Targeted analysis of polymorphic loci from low-coverage shotgun sequence data allows accurate genotyping of HLA genes in historical human populations

The highly polymorphic human leukocyte antigen (HLA) plays a crucial role in adaptive immunity and is associated with various complex diseases. Accurate analysis of HLA genes using ancient DNA (aDNA) data is crucial for understanding their role in human adaptation to pathogens. Here, we describe the TARGT pipeline for targeted analysis of polymorphic loci from low-coverage shotgun sequence data. The pipeline was successfully applied to medieval aDNA samples and validated using both simulated aDNA and modern empirical sequence data from the 1000 Genomes Project. Thus the TARGT pipeline enables accurate analysis of HLA polymorphisms in historical (and modern) human populations

Allen's Interval Algebra Makes the Difference

Allen's Interval Algebra constitutes a framework for reasoning about temporal information in a qualitative manner. In particular, it uses intervals, i.e., pairs of endpoints, on the timeline to represent entities corresponding to actions, events, or tasks, and binary relations such as precedes and overlaps to encode the possible configurations between those entities. Allen's calculus has found its way in many academic and industrial applications that involve, most commonly, planning and scheduling, temporal databases, and healthcare. In this paper, we present a novel encoding of Interval Algebra using answer-set programming (ASP) extended by difference constraints, i.e., the fragment abbreviated as ASP(DL), and demonstrate its performance via a preliminary experimental evaluation. Although our ASP encoding is presented in the case of Allen's calculus for the sake of clarity, we suggest that analogous encodings can be devised for other point-based calculi, too.Comment: Part of DECLARE 19 proceeding

The proton radius puzzle

High-precision measurements of the proton radius from laser spectroscopy of muonic hydrogen demonstrated up to six standard deviations smaller values than obtained from electron-proton scattering and hydrogen spectroscopy. The status of this discrepancy, which is known as the proton radius puzzle will be discussed in this paper, complemented with the new insights obtained from spectroscopy of muonic deuterium.Comment: Moriond 2017 conference, 8 pages, 4 figure

Associations between the time of conception and the shape of the lactation curve in early lactation in Norwegian dairy cattle

<p>Abstract</p> <p>Background</p> <p>This study was carried out to determine if an association exists between the shape of the lactation curve before it is influenced by the event of conception and the time from calving to conception in Norwegian dairy cattle. Lactation curves of Norwegian Red cows during 5 to 42 days in milk (DIM) were compared between cows conceiving between 43 and 93 DIM and cows conceiving after 93 DIM.</p> <p>Methods</p> <p>Data from 23,049 cows, represented by one lactation each, with 219,538 monthly test days were extracted from the Norwegian Dairy Herd Recording System, which represents 97% of all Norwegian dairy cows. Besides veterinary treatments, these records also included information on daily milk yield at monthly test days. The data were stratified by parity groups (1, 2, and 3 and higher) and time to conception periods (43-93 DIM and >93 DIM). The sample was selected using the following selection criteria: conception later than 42 DIM, calving season July to September, no records of veterinary treatment and the level of energy fed as concentrates between 8.69 and 12.83 MJ. The shape of the lactation curves were parameterized using a modified Wilmink-model in a mixed model analysis. Differences in the parameters of the lactation curves with different conception times were evaluated using confidence intervals.</p> <p>Results</p> <p>Lactation curves characterized by a low intercept and a steep ascending slope and a steep descending slope were associated with early conception across all parities. The peak milk yield was not associated with time of conception.</p> <p>Conclusions</p> <p>A practical application of the study results is the use of the shape of the lactation curve in future herd management. Groups of cows with impaired reproductive performance may be identified due to an unfavorable shape of the lactation curve. Monitoring lactation curves and adjusting the feeding strategy to adjust yield therefore may be useful for the improvement of reproductive performance at herd level.</p

HemeBIND: a novel method for heme binding residue prediction by combining structural and sequence information

<p>Abstract</p> <p>Background</p> <p>Accurate prediction of binding residues involved in the interactions between proteins and small ligands is one of the major challenges in structural bioinformatics. Heme is an essential and commonly used ligand that plays critical roles in electron transfer, catalysis, signal transduction and gene expression. Although much effort has been devoted to the development of various generic algorithms for ligand binding site prediction over the last decade, no algorithm has been specifically designed to complement experimental techniques for identification of heme binding residues. Consequently, an urgent need is to develop a computational method for recognizing these important residues.</p> <p>Results</p> <p>Here we introduced an efficient algorithm HemeBIND for predicting heme binding residues by integrating structural and sequence information. We systematically investigated the characteristics of binding interfaces based on a non-redundant dataset of heme-protein complexes. It was found that several sequence and structural attributes such as evolutionary conservation, solvent accessibility, depth and protrusion clearly illustrate the differences between heme binding and non-binding residues. These features can then be separately used or combined to build the structure-based classifiers using support vector machine (SVM). The results showed that the information contained in these features is largely complementary and their combination achieved the best performance. To further improve the performance, an attempt has been made to develop a post-processing procedure to reduce the number of false positives. In addition, we built a sequence-based classifier based on SVM and sequence profile as an alternative when only sequence information can be used. Finally, we employed a voting method to combine the outputs of structure-based and sequence-based classifiers, which demonstrated remarkably better performance than the individual classifier alone.</p> <p>Conclusions</p> <p>HemeBIND is the first specialized algorithm used to predict binding residues in protein structures for heme ligands. Extensive experiments indicated that both the structure-based and sequence-based methods have effectively identified heme binding residues while the complementary relationship between them can result in a significant improvement in prediction performance. The value of our method is highlighted through the development of HemeBIND web server that is freely accessible at <url>http://mleg.cse.sc.edu/hemeBIND/</url>.</p

Chemical vapour deposition synthetic diamond: materials, technology and applications

Substantial developments have been achieved in the synthesis of chemical vapour deposition (CVD) diamond in recent years, providing engineers and designers with access to a large range of new diamond materials. CVD diamond has a number of outstanding material properties that can enable exceptional performance in applications as diverse as medical diagnostics, water treatment, radiation detection, high power electronics, consumer audio, magnetometry and novel lasers. Often the material is synthesized in planar form, however non-planar geometries are also possible and enable a number of key applications. This article reviews the material properties and characteristics of single crystal and polycrystalline CVD diamond, and how these can be utilized, focusing particularly on optics, electronics and electrochemistry. It also summarizes how CVD diamond can be tailored for specific applications, based on the ability to synthesize a consistent and engineered high performance product.Comment: 51 pages, 16 figure

COVIDiSTRESS Global Survey dataset on psychological and behavioural consequences of the COVID-19 outbreak

This N = 173,426 social science dataset was collected through the collaborative COVIDiSTRESS Global Survey – an open science effort to improve understanding of the human experiences of the 2020 COVID-19 pandemic between 30th March and 30th May, 2020. The dataset allows a cross-cultural study of psychological and behavioural responses to the Coronavirus pandemic and associated government measures like cancellation of public functions and stay at home orders implemented in many countries. The dataset contains demographic background variables as well as measures of Asian Disease Problem, perceived stress (PSS-10), availability of social provisions (SPS-10), trust in various authorities, trust in governmental measures to contain the virus (OECD trust), personality traits (BFF-15), information behaviours, agreement with the level of government intervention, and compliance with preventive measures, along with a rich pool of exploratory variables and written experiences. A global consortium from 39 countries and regions worked together to build and translate a survey with variables of shared interests, and recruited participants in 47 languages and dialects. Raw plus cleaned data and dynamic visualizations are available

Traditional knowledge of wild edible plants used in the northwest of the Iberian Peninsula (Spain and Portugal): a comparative study

<p>Abstract</p> <p>Background</p> <p>We compare traditional knowledge and use of wild edible plants in six rural regions of the northwest of the Iberian Peninsula as follows: Campoo, Picos de Europa, Piloña, Sanabria and Caurel in Spain and Parque Natural de Montesinho in Portugal.</p> <p>Methods</p> <p>Data on the use of 97 species were collected through informed consent semi-structured interviews with local informants. A semi-quantitative approach was used to document the relative importance of each species and to indicate differences in selection criteria for consuming wild food species in the regions studied.</p> <p>Results and discussion</p> <p>The most significant species include many wild berries and nuts (e.g. <it>Castanea sativa, Rubus ulmifolius, Fragaria vesca</it>) and the most popular species in each food-category (e.g. fruits or herbs used to prepare liqueurs such as <it>Prunus spinosa</it>, vegetables such as <it>Rumex acetosa</it>, condiments such as <it>Origanum vulgare</it>, or plants used to prepare herbal teas such as <it>Chamaemelum nobile</it>). The most important species in the study area as a whole are consumed at five or all six of the survey sites.</p> <p>Conclusion</p> <p>Social, economic and cultural factors, such as poor communications, fads and direct contact with nature in everyday life should be taken into account in determining why some wild foods and traditional vegetables have been consumed, but others not. They may be even more important than biological factors such as richness and abundance of wild edible flora. Although most are no longer consumed, demand is growing for those regarded as local specialties that reflect regional identity.</p