Personalized machine learning approach to injury monitoring in elite volleyball players.

We implemented a machine learning approach to investigate individual indicators of training load and wellness that may predict the emergence or development of overuse injuries in professional volleyball. In this retrospective study, we collected data of 14 elite volleyball players (mean ± SD age: 27 ± 3 years, weight: 90.5 ± 6.

Tackling the challenges of bioimage analysis.

Using multiple human annotators and ensembles of trained networks can improve the performance of deep-learning methods in research.

Insertions of codons encoding basic amino acids in H7 hemagglutinins of influenza A viruses occur by recombination with RNA at hotspots near snoRNA binding sites.

The presence of multiple basic amino acids in the protease cleavage site of the hemagglutinin (HA) protein is the main molecular determinant of virulence of highly pathogenic avian influenza (HPAI) viruses. Recombination of HA RNA with other RNA molecules of host or virus origin is a dominant mechanism of multibasic cleavage site (MBCS) acquisition for H7 subtype HA. Using alignments of HA RNA sequences from documented cases of MBCS insertion due to recombination, we show that such recombination with host RNAs is most likely to occur at particular hotspots in ribosomal RNAs (rRNAs), transfer RNAs (tRNAs), and viral RNAs.

Xrn1-resistant RNA structures are well-conserved within the genus flavivirus.

Subgenomic RNAs are produced by several RNA viruses through incomplete degradation of their genomic RNA by the exoribonuclease Xrn1, and have been shown to be essential for viral growth and pathogenicity. Within the flavivirus genus of the family, two distinct classes of Xrn1-resistant RNA motifs have been proposed; one for mosquito-borne and insect-specific flaviviruses, and one for tick-borne flaviviruses and no-known-vector flaviviruses. We investigated tick-borne and no-known-vector flavivirus Xrn1-resistant RNA motifs through systematic mutational analysis and showed that both classes actually possess very similar structural configurations, including a double pseudoknot and a base-triple at identical, conserved locations.

A database of flavivirus RNA structures with a search algorithm for pseudoknots and triple base interactions.

Motivation: The Flavivirus genus includes several important pathogens, such as Zika, dengue and yellow fever virus. Flavivirus RNA genomes contain a number of functionally important structures in their 3' untranslated regions (3'UTRs). Due to the diversity of sequences and topologies of these structures, their identification is often difficult.

Anti-tuberculosis effect of isoniazid scales accurately from zebrafish to humans.

Background And Purpose: There is a clear need for innovation in anti-tuberculosis drug development. The zebrafish larva is an attractive disease model in tuberculosis research. To translate pharmacological findings to higher vertebrates, including humans, the internal exposure of drugs needs to be quantified and linked to observed response.

Articles with impact: insights into 10 years of research with machine learning.

Worldwide scientific output is growing faster and faster. Academics should not only publish much and fast, but also publish research with impact. The aim of this study is to use machine learning to investigate characteristics of articles that were published in the between 2009 and 2018, and characterize high-impact articles.

DeepVF: a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy.

Virulence factors (VFs) enable pathogens to infect their hosts. A wealth of individual, disease-focused studies has identified a wide variety of VFs, and the growing mass of bacterial genome sequence data provides an opportunity for computational methods aimed at predicting VFs. Despite their attractive advantages and performance improvements, the existing methods have some limitations and drawbacks.

First results of a ferritin-based blood donor deferral policy in the Netherlands.

Background: Whole blood donors are at risk of becoming iron deficient. To monitor iron stores, Sanquin implemented a new deferral policy based on ferritin levels, in addition to the traditional hemoglobin measurements.

Methods: Ferritin levels are determined in every fifth donation, as well as in all first-time donors.

Fungal metabarcoding data integration framework for the MycoDiversity DataBase (MDDB).

Fungi have crucial roles in ecosystems, and are important associates for many organisms. They are adapted to a wide variety of habitats, however their global distribution and diversity remains poorly documented. The exponential growth of DNA barcode information retrieved from the environment is assisting considerably the traditional ways for unraveling fungal diversity and detection.

Homophily in Personality Enhances Group Success Among Real-Life Friends.

Personality affects dyadic relations and teamwork, yet its role among groups of friends has been little explored. We examine for the first time whether similarity in personality enhances the effectiveness of real-life friendship groups. Using data from a longitudinal study of a European fraternity (10 male and 15 female groups), we investigate how individual Big Five personality traits were associated with group formation and whether personality homophily related to how successful the groups were over 1 year ( = 147-196).

Automated image analysis system for studying cardiotoxicity in human pluripotent stem cell-Derived cardiomyocytes.

Background: Cardiotoxicity, characterized by severe cardiac dysfunction, is a major problem in patients treated with different classes of anticancer drugs. Development of predictable human-based models and assays for drug screening are crucial for preventing potential drug-induced adverse effects. Current animal in vivo models and cell lines are not always adequate to represent human biology.

Successive Statistical and Structure-Based Modeling to Identify Chemically Novel Kinase Inhibitors.

Kinases are frequently studied in the context of anticancer drugs. Their involvement in cell responses, such as proliferation, differentiation, and apoptosis, makes them interesting subjects in multitarget drug design. In this study, a workflow is presented that models the bioactivity spectra for two panels of kinases: (1) inhibition of RET, BRAF, SRC, and S6K, while avoiding inhibition of MKNK1, TTK, ERK8, PDK1, and PAK3, and (2) inhibition of AURKA, PAK1, FGFR1, and LKB1, while avoiding inhibition of PAK3, TAK1, and PIK3CA.

MSIsensor-pro: Fast, Accurate, and Matched-normal-sample-free Detection of Microsatellite Instability.

Microsatellite instability (MSI) is a key biomarker for cancer therapy and prognosis. Traditional experimental assays are laborious and time-consuming, and next-generation sequencing-based computational methods do not work on leukemia samples, paraffin-embedded samples, or patient-derived xenografts/organoids, due to the requirement of matched normal samples. Herein, we developed MSIsensor-pro, an open-source single sample MSI scoring method for research and clinical applications.

Anthropometric Clusters of Competitive Cyclists and Their Sprint and Endurance Performance.

Do athletes specialize toward sports disciplines that are well aligned with their anthropometry? Novel machine-learning algorithms now enable scientists to cluster athletes based on their individual anthropometry while integrating multiple anthropometric dimensions, which may provide new perspectives on anthropometry-dependent sports specialization. We aimed to identify clusters of competitive cyclists based on their individual anthropometry using multiple anthropometric measures, and to evaluate whether athletes with a similar anthropometry also competed in the same cycling discipline. Additionally, we assessed differences in sprint and endurance performance between the anthropometric clusters.

Conserved structural RNA domains in regions coding for cleavage site motifs in hemagglutinin genes of influenza viruses.

The acquisition of a multibasic cleavage site (MBCS) in the hemagglutinin (HA) glycoprotein is the main determinant of the conversion of low pathogenic avian influenza viruses into highly pathogenic strains, facilitating HA cleavage and virus replication in a broader range of host cells. In nature, substitutions or insertions in HA RNA genomic segments that code for multiple basic amino acids have been observed only in the HA genes of two out of sixteen subtypes circulating in birds, H5 and H7. Given the compatibility of MBCS motifs with HA proteins of numerous subtypes, this selectivity was hypothesized to be determined by the existence of specific motifs in HA RNA, in particular structured domains.

The reach of commercially motivated junk news on Facebook.

Commercially motivated junk news-i.e. money-driven, highly shareable clickbait with low journalistic production standards-constitutes a vast and largely unexplored news media ecosystem.

A probabilistic framework for predicting disease dynamics: A case study of psychotic depression.

Unsupervised learning is often used to obtain insight into the underlying structure of medical data, but it is not always clear how to use such structure in an effective way. In this paper, we propose a probabilistic framework for predicting disease dynamics guided by latent states. The framework is based on hidden Markov models and aims to facilitate the selection of hypotheses that might yield insight into the dynamics.

Analyzing Empowerment Processes Among Cancer Patients in an Online Community: A Text Mining Approach.

Background: Peer-to-peer online support groups and the discussion forums in these groups can help patients by providing opportunities for increasing their empowerment. Most previous research on online empowerment and online social support uses qualitative methods or questionnaires to gain insight into the dynamics of online empowerment processes.

Objective: The overall goal of this study was to analyze the presence of the empowerment processes in the online peer-to-peer communication of people affected by cancer, using text mining techniques.

Structural features of an Xrn1-resistant plant virus RNA.

Xrn1 is a major 5'-3' exoribonuclease involved in the RNA metabolism of many eukaryotic species. RNA viruses have evolved ways to thwart Xrn1 in order to produce subgenomic non-coding RNA that affects the hosts RNA metabolism. The 3' untranslated region of several beny- and cucumovirus RNAs harbors a so-called 'coremin' motif that is required for Xrn1 stalling.

Finding Dutch natives in online forums.

Law enforcement agencies have a restricted area in which their powers apply, which is called their jurisdiction. These restrictions also apply to the Internet. However, on the Internet, the physical borders of the jurisdiction, typically country borders, are hard to discover.

Automated Algorithm Selection: Survey and Perspectives.

It has long been observed that for practically any computational problem that has been intensely studied, different instances are best solved using different algorithms. This is particularly pronounced for computationally hard problems, where in most cases, no single algorithm defines the state of the art; instead, there is a set of algorithms with complementary strengths. This performance complementarity can be exploited in various ways, one of which is based on the idea of selecting, from a set of given algorithms, for each problem instance to be solved the one expected to perform best.