Informal traders lock horns with the formal milk industry: the role of research in pro-poor dairy policy shift in Kenya

A polarizable atomic multipole-based force field for the membrane bilayer models 1,2-dioleoyl-phosphocholine (DOPC) and 1-palmitoyl-2-oleoyl-phosphatidylethanolamine (POPE) has been developed. The force field adopts the same framework as the Atomic Multipole Optimized Energetics for Biomolecular Applications (AMOEBA) model, in which the charge distribution of each atom is represented by the permanent atomic monopole, dipole and quadrupole moments. Many-body polarization including the inter- and intra-molecular polarization is modelled in a consistent manner with distributed atomic polarizabilities. The van der Waals parameters were first transferred from existing AMOEBA parameters for small organic molecules and then optimised by fitting to ab initio intermolecular interaction energies between models and a water molecule. Molecular dynamics simulations of the two aqueous DOPC and POPE membrane bilayer systems, consisting of 72 model molecules, were then carried out to validate the force field parameters. Membrane width, area per lipid, volume per lipid, deuterium order parameters, electron density profile, etc. were consistent with experimental values

Prediction and Validation of a Protein’s Free Energy Surface Using Hydrogen Exchange and (Importantly) Its Denaturant Dependence

The denaturant dependence of hydrogen–deuterium exchange (HDX) is a powerful measurement to identify the breaking of individual H-bonds and map the free energy surface (FES) of a protein including the very rare states. Molecular dynamics (MD) can identify each partial unfolding event with atomic-level resolution. Hence, their combination provides a great opportunity to test the accuracy of simulations and to verify the interpretation of HDX data. For this comparison, we use Upside, our new and extremely fast MD package that is capable of folding proteins with an accuracy comparable to that of all-atom methods. The FESs of two naturally occurring and two designed proteins are so generated and compared to our NMR/HDX data. We find that Upside’s accuracy is considerably improved upon modifying the energy function using a new machine-learning procedure that trains for proper protein behavior including realistic denatured states in addition to stable native states. The resulting increase in cooperativity is critical for replicating the HDX data and protein stability, indicating that we have properly encoded the underlying physiochemical interactions into an MD package. We did observe some mismatch, however, underscoring the ongoing challenges faced by simulations in calculating accurate FESs. Nevertheless, our ensembles can identify the properties of the fluctuations that lead to HDX, whether they be small-, medium-, or large-scale openings, and can speak to the breadth of the native ensemble that has been a matter of debate

Bioactive Constituents of Verbena officinalis Alleviate Inflammation and Enhance Killing Efficiency of Natural Killer Cells

Natural killer (NK) cells play key roles in eliminating pathogen-infected cells. Verbena officinalis (V. officinalis) has been used as a medical plant in traditional and modern medicine for its anti-tumor and anti-inflammatory activities, but its effects on immune responses remain largely elusive. This study aimed to investigate the potential of V. officinalis extract (VO extract) to regulate inflammation and NK cell functions. We examined the effects of VO extract on lung injury in a mouse model of influenza virus infection. We also investigated the impact of five bioactive components of VO extract on NK killing functions using primary human NK cells. Our results showed that oral administration of VO extract reduced lung injury, promoted the maturation and activation of NK cells in the lung, and decreased the levels of inflammatory cytokines (IL-6, TNF-α and IL-1β) in the serum. Among five bioactive components of VO extract, Verbenalin significantly enhanced NK killing efficiency in vitro, as determined by real-time killing assays based on plate-reader or high-content live-cell imaging in 3D using primary human NK cells. Further investigation showed that treatment of Verbenalin accelerated the killing process by reducing the contact time of NK cells with their target cells without affecting NK cell proliferation, expression of cytotoxic proteins, or lytic granule degranulation. Together, our findings suggest that VO extract has a satisfactory anti-inflammatory effect against viral infection in vivo, and regulates the activation, maturation, and killing functions of NK cells. Verbenalin from V. officinalis enhances NK killing efficiency, suggesting its potential as a promising therapeutic to fight viral infection

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Polarizable force field development for lipids and their efficient applications in membrane proteins

Polarizable force fields have been developed due to the intrinsic problem of additive force fields in modeling electrostatic interactions. Because of the capability to accurately describe the behavior of systems with significant changes in their electrostatic environments, polarizable force fields might be a decent tool to study membrane-related systems, such as lipid bilayers, though not so much progresses have been made. In this overview article we described the developments of a variety of polarizable force fields, including the corresponding theories, benchmark examples, and more specifically we were focused on the applications on lipid membranes. (C) 2017 John Wiley & Sons, Lt

Free Energy Simulations with the AMOEBA Polarizable Force Field and Metadynamics on GPU Platform

The free energy calculation library PLUMED has been incorporated into the OpenMM simulation toolkit, with the purpose to perform enhanced sampling MD simulations using the AMOEBA polarizable force field on GPU platform. Two examples, (I) the free energy profile of water pair separation (II) alanine dipeptide dihedral angle free energy surface in explicit solvent, are provided here to demonstrate the accuracy and efficiency of our implementation. The converged free energy profiles could be obtained within an affordable MD simulation time when the AMOEBA polarizable force field is employed. Moreover, the free energy surfaces estimated using the AMOEBA polarizable force field are in agreement with those calculated from experimental data and ab initio methods. Hence, the implementation in this work is reliable and would be utilized to study more complicated biological phenomena in both an accurate and efficient way. (C) 2015 Wiley Periodicals, Inc

Factors That Control the Force Needed to Unfold a Membrane Protein in Silico Depend on the Mode of Denaturation

Single-molecule force spectroscopy methods, such as AFM and magnetic tweezers, have proved extremely beneficial in elucidating folding pathways for soluble and membrane proteins. To identify factors that determine the force rupture levels in force-induced membrane protein unfolding, we applied our near-atomic-level Upside molecular dynamics package to study the vertical and lateral pulling of bacteriorhodopsin (bR) and GlpG, respectively. With our algorithm, we were able to selectively alter the magnitudes of individual interaction terms and identify that, for vertical pulling, hydrogen bond strength had the strongest effect, whereas other non-bonded protein and membrane–protein interactions had only moderate influences, except for the extraction of the last helix where the membrane–protein interactions had a stronger influence. The up–down topology of the transmembrane helices caused helices to be pulled out as pairs. The rate-limiting rupture event often was the loss of H-bonds and the ejection of the first helix, which then propagated tension to the second helix, which rapidly exited the bilayer. The pulling of the charged linkers across the membrane had minimal influence, as did changing the bilayer thickness. For the lateral pulling of GlpG, the rate-limiting rupture corresponded to the separation of the helices within the membrane, with the H-bonds generally being broken only afterward. Beyond providing a detailed picture of the rupture events, our study emphasizes that the pulling mode greatly affects the factors that determine the forces needed to unfold a membrane protein

Introducing Improved Transformer to Land Cover Classification Using Multispectral LiDAR Point Clouds

The use of Transformer-based networks has been proposed for the processing of general point clouds. However, there has been little research related to multispectral LiDAR point clouds that contain both spatial coordinate information and multi-wavelength intensity information. In this paper, we propose networks for multispectral LiDAR point cloud point-by-point classification based on an improved Transformer. Specifically, considering the sparseness of different regions of multispectral LiDAR point clouds, we add a bias to the Transformer to improve its ability to capture local information and construct an easy-to-implement multispectral LiDAR point cloud Transformer (MPT) classification network. The MPT network achieves 78.49% mIoU, 94.55% OA, 84.46% F1, and 0.92 Kappa on the multispectral LiDAR point cloud testing dataset. To further extract the topological relationships between points, we present a standardization set abstraction (SSA) module, which includes the global point information while considering the relationships among the local points. Based on the SSA module, we propose an advanced version called MPT+ for the point-by-point classification of multispectral LiDAR point clouds. The MPT+ network achieves 82.94% mIoU, 95.62% OA, 88.42% F1, and 0.94 Kappa on the same testing dataset. Compared with seven point-based deep learning algorithms, our proposed MPT+ achieves state-of-the-art results for several evaluation metrics

A Polarizable Atomic Multipole-Based Force Field for Molecular Dynamics Simulations of Anionic Lipids

In all of the classical force fields, electrostatic interaction is simply treated and explicit electronic polarizability is neglected. The condensed-phase polarization, relative to the gas-phase charge distributions, is commonly accounted for in an average way by increasing the atomic charges, which remain fixed throughout simulations. Based on the lipid polarizable force field DMPC and following the same framework as Atomic Multipole Optimized Energetics for BiomoleculAr (AMOEBA) simulation, the present effort expands the force field to new anionic lipid models, in which the new lipids contain DMPG and POPS. The parameters are compatible with the AMOEBA force field, which includes water, ions, proteins, etc. The charge distribution of each atom is represented by the permanent atomic monopole, dipole and quadrupole moments, which are derived from the ab initio gas phase calculations. Many-body polarization including the inter- and intramolecular polarization is modeled in a consistent manner with distributed atomic polarizabilities. Molecular dynamics simulations of the two aqueous DMPG and POPS membrane bilayer systems, consisting of 72 lipids with water molecules, were then carried out to validate the force field parameters. Membrane width, area per lipid, volume per lipid, deuterium order parameters, electron density profile, electrostatic potential difference between the center of the bilayer and water are all calculated, and compared with limited experimental data

The Impact of the Allocation of Facilities on Reducing Carbon Emissions from a Green Container Terminal Perspective

The main contribution of this paper is to quantify the impact of the allocation of facilities, including the number of facilities and the fuels adopted by facilities, on carbon emissions. In order to deal with the complex queuing network of container terminals, a simulation model is established with the changing of the number of and the fuel adopted by facilities as inputs. Firstly, the operation process and complex queuing network of container terminals are described to explain why simulation technology needs to be used. Then, various simulation experiments based on a container terminal in Algeria are designed and carried out. Finally, the carbon emissions from facilities and ships at berth and inside container terminals, and the total carbon emissions inside container terminals, are obtained and analyzed. Results show that the emissions from facilities are only a small fraction of the total emissions of container terminals. Improving the number of trucks and yard cranes can help reduce carbon emissions, but when the number continues to rise, the emissions are decreased very slightly. The results obtained and proposed method can be applied to build a green container terminal, which can also be used for similar problems