Is there a future for cell-free fetal dna tests in screening for preeclampsia?

CffDNA screening is a powerful diagnostic tool in the prenatal diagnosis algorithm for chromosomal abnormalities. With detailed ultrasound examination as the mainstay of first-trimester risk assessment, cffDNA has been shown to be superior to first-trimester combined screening (FTCS) in false-positive rates for trisomy 21 detection. In light of the growing interest in cffDNA testing and the possibility of it replacing first-trimester biochemistry, we decided to investigate the usefulness of cffDNA tests in early-pregnancy risk assessment for preeclampsia (PE). The aim of this review paper was to evaluate clinical application of first-trimester cfDNA in predicting PE, as well as to investigate its possible use in first-trimester PE screening enhancement, also in cases where biochemistry is not performed.

The practical use of acetylsalicylic acid in the era of the ASPRE trial. Update and literature review

It is now well established that acetylsalicylic acid — one of the most widely prescribed drugs today — has brought a new era in maternal-fetal medicine. The History of medicine mentions several antecedents. Extracts made from willow contained in clay tablets are reported in both ancient Sumer and Egypt. In 400 BC, Hippocrates referred to the use of salicylic tea to reduce fevers. In the 1950s, acetylsalicylic acid entered the Guinness Book of Records as the highest selling painkiller. There is little doubt that acetylsalicylic acid — one of the first drugs to enter common usage — remains one of the most researched drugs in the world

Conformations of Flanking Bases in HIV-1 RNA DIS Kissing Complexes Studied by Molecular Dynamics

Explicit solvent molecular dynamics simulations (in total almost 800 ns including locally enhanced sampling runs) were applied with different ion conditions and with two force fields (AMBER and CHARMM) to characterize typical geometries adopted by the flanking bases in the RNA kissing-loop complexes. We focus on flanking base positions in multiple x-ray and NMR structures of HIV-1 DIS kissing complexes and kissing complex from the large ribosomal subunit of Haloarcula marismortui. An initial x-ray open conformation of bulged-out bases in HIV-1 DIS complexes, affected by crystal packing, tends to convert to a closed conformation formed by consecutive stretch of four stacked purine bases. This is in agreement with those recent crystals where the packing is essentially avoided. We also observed variants of the closed conformation with three stacked bases, while nonnegligible populations of stacked geometries with bulged-in bases were detected, too. The simulation results reconcile differences in positions of the flanking bases observed in x-ray and NMR studies. Our results suggest that bulged-out geometries are somewhat more preferred, which is in accord with recent experiments showing that they may mediate tertiary contacts in biomolecular assemblies or allow binding of aminoglycoside antibiotics

Evolution of communities of software: using tensor decompositions to compare software ecosystems

© 2019 The Authors. Published by Springer. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1007/s41109-019-0193-5Modern software development is often a collaborative effort involving many authors through the re-use and sharing of code through software libraries. Modern software “ecosystems” are complex socio-technical systems which can be represented as a multilayer dynamic network. Many of these libraries and software packages are open-source and developed in the open on sites such as , so there is a large amount of data available about these networks. Studying these networks could be of interest to anyone choosing or designing a programming language. In this work, we use tensor factorisation to explore the dynamics of communities of software, and then compare these dynamics between languages on a dataset of approximately 1 million software projects. We hope to be able to inform the debate on software dependencies that has been recently re-ignited by the malicious takeover of the npm package and other incidents through giving a clearer picture of the structure of software dependency networks, and by exploring how the choices of language designers—for example, in the size of standard libraries, or the standards to which packages are held before admission to a language ecosystem is granted—may have shaped their language ecosystems. We establish that adjusted mutual information is a valid metric by which to assess the number of communities in a tensor decomposition and find that there are striking differences between the communities found across different software ecosystems and that communities do experience large and interpretable changes in activity over time. The differences between the elm and R software ecosystems, which see some communities decline over time, and the more conventional software ecosystems of Python, Java and JavaScript, which do not see many declining communities, are particularly marked.OAB’s work was supported as part of an Engineering and Physical Sciences Research Council (EPSRC) grant, project reference EP/I028099/1.Published versio

Spatial community structure and epidemics

Networks are a useful quantitative representation for complex systems of interacting entities arising in fields such as biological, physical and social sciences. A network representation provides a degree of simplification while capturing key connectivity patterns. This thesis focuses on two main themes: the study of community structure, an important mesoscopic feature of many networks, and its application to study spatiotemporal spread of infectious diseases. Community detection seeks to partition a network into dense sets of nodes that are connected sparsely to other dense sets. The notion of denseness is often relative to some "null model" that describes baseline connectivity that can be construed to occur randomly. In the first part of the thesis, we discuss the incorporation of spatial information into null models for community detection. We develop a spatial null model based on the radiation model of mobility. We test different spatial null models using static and temporal (multilayer) spatial benchmarks with planted partitions that represent interactions between human populations. Our results indicate that it is important to incorporate spatial information into null models for community detection, but it is best to incorporate only relevant information into null models, as extraneous information can lower performance. In the second part of the thesis, we present the results of community detection with different null models on disease-correlation networks generated form real and synthetic time series of disease occurrence. We use data sets for endemic diseases (established in a region, with occasional epidemic outbreaks) and emerging diseases (newly-discovered or introduced into a region for the first time). We study the spatial and temporal organization of partitions. Finally, we apply community detection with different null models to synthetic time series generated from an agent-based model (ABM) simulating the spread of endemic and emerging diseases between spatially-embedded cities with a planted, transport-based community structure. We compare the findings on real and synthetic data sets, and we searched for model parameter regimes in which we are able to detect planted partitions or other interesting communities. For emerging diseases, we find spatial communities that are associated with the first times the infection reached a node in both ABM and disease data. For endemic diseases, we are unable to find planted or spatial communities in the ABM data, but we detect spatial communities for two of the three disease data sets. For these diseases, we also detect temporal communities corresponding to some of the important time points in disease history. We hope that these results show that community structure of disease correlation networks appears to be more complicated than simple spatial patterns and is a fascinating topic to study.</p

The influence of the breed and age of boars on the occurrence of selected morphological defects of sperm in semen

W niniejszej pracy dokonano oceny wpływu rasy i wieku knura na wybrane wady morfologiczne plemników. Wykazano istotny wpływ rasy i wariantu krzyżowania z którego pochodzi knur oraz jego wieku na odsetek występowania podstawowych wad morfologicznych plemników w nasieniu. Stwierdzono, że najlepszym nasieniem charakteryzowały się knury rasy wielkiej białej polskiej. Najwyższy odsetek plemników z wadami łącznie stwierdzono w ejakulatach knurów pietrain, w wieku 24–36 miesięcy, następnie u knurów rasy polskiej białej zwisłouchej w wieku 24–36 miesięcy.In this work the influence of the breed and age of boars on selected defects of sperm is estimated. It is shown that the breed and the variant of the crossing from which the boar comes, as well as his age, have a significant impact on the percentage of occurrence of the basis morphological defects of sperm in semen. It has been proved that Polish Large White breed boars are characterised by the best sperm. The highest percentage of sperm with defects characterised Pietrain boars aged 24–36 months, followed by Polish Landrace boars aged 24–36 months, and those over 36 months