bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Methodological Framework to Assess the Accuracy of Virtual Reality Hand-Tracking Systems: A case study with the Oculus Quest 2
Authors: Abdlkarim Diar , Di Luca Massimiliano , Aves Poppy , Yeo Sang-Hoon , Miall R. Chris , Holland Peter , Galea Joseph M. 
Published: February 2022

AbstractOptical marker-less hand-tracking systems incorporated into virtual reality (VR) headsets are transforming the ability to assess motor skills, including hand movements, in VR. This promises to have far-reaching implications for the increased applicability of VR across scientific, industrial and clinical settings. However, so far, there is little data regarding the accuracy, delay and overall performance of these types of hand-tracking systems. Here we present a novel methodological framework which can be easily applied to measure these systems’ absolute positional error, temporal delay and finger joint-angle accuracy. We used this framework to evaluate the Meta Quest 2 hand-tracking system. Our results showed an average fingertip positional error of 1.1cm, an average finger joint angle error of 9.6oand an average temporal delay of 38.0ms. Finally, a novel approach was developed to correct for these positional errors based on a lens distortion model. This methodological framework provides a powerful tool to ensure the reliability and validity of data originating from VR-based, marker-less hand-tracking systems.
Hyperflexion is unlikely to be the primary cervical spine injury mechanism in accidental head-on rugby tackling
Authors: Silvestros Pavlos , Preatoni Ezio , Gill Harinderjit S. , Cazzola Dario 
Published: February 2022

AbstractIn Rugby a high proportion of catastrophic cervical spine injuries occur during tackling. In the injury prevention literature, there is still an open debate on the injury mechanisms related to such injuries, with hyperflexion and buckling being under scrutiny. The aims of this study were to determine the primary cervical spine injury mechanism during head-on rugby tackling, and evaluate the effect of tackling technique on cervical spine intervertebral loading. We conducted an in silico study to examine the dynamic response of the cervical spine under loading conditions representative of accidental head-on rugby tackles by using a subject-specific musculoskeletal model of a rugby player. The computer simulations were driven by experimental in vivo data of an academy rugby player tackling a punchbag, and in vitro data of head-first impacts using a dummy head. Results showed that: i) the earlier generation of high compression and anterior shear loads with low values of flexion moments provides evidence that hyperflexion is unlikely to be the primary injury mechanism in the sub-axial cervical spine (C3-C7) during central and posterior head impact locations; ii) a higher degree of neck flexion at impact poses the cervical spine in a more hazardous position. These findings provide objective evidence to inform injury prevention strategies or rugby law changes, with the final view of improving the safety of the game of rugby.
Differential binding of salicylic acid, phenolic acid derivatives and co-factors determines the roles of Arabidopsis NPR1 to NPR4 in plant immunity
Authors: Konopka Evelyn , Saur Mathias , Pfitzner Artur J.P. , Pfitzner Ursula M. 
Published: February 2022

SummaryGenetic studies have demonstrated that NPR1 is the key positive regulator of salicylic acid (SA)-induced PR-1 gene induction and systemic acquired resistance (SAR). In Arabidopsis, family members NPR1 to NPR4 share domain architecture.Yeast hybrid assays were used to explore biochemical capabilities of NPR1 to NPR4.All NPR1 to NPR4 are responsive to SA. SA perception proceeds via the conserved arginine embedded in a C-terminal LENRV-like motif. Clade 2 proteins NPR3 and NPR4 perceive SA directly, while clade 1 members NPR1 and NPR2 require interaction with partner proteins NIMIN1/NIMIN2 and TGA factors, respectively, to enable SA sensing. Intriguingly, NPR3 is considerably more sensitive to the synthetic analog 3,5-dichloroanthranilic acid than to SA, and all NPR1 to NPR4 are able to sense the microbial metabolite 6-methyl SA.We suggest that the plant´s ability to track SA and phenolic acid derivatives through NPR proteins has evolved to support diverse defense signaling outputs that are activated in parallel by agonists which may be of microbial or plant origin. In this line, NPR1-NIMIN2/NIMIN1 complex is the prime receptor for SA synthesized by plants in response to microbial attack, while NPR3 induces defense different from SAR primarily via unrecognized signal molecules.
Progressive maturation of the root apical meristem inArabidopsis thalianalateral roots
Authors: Berthet Béatrice , Bald Lotte , Louveaux Marion , Maizel Alexis 
Published: February 2022

AbstractMeristems are stem cells niches that support the formation of all plant organs and are either set during embryogenesis and maintained throughout the plant life or specified de novo, post-embryonically. The embryo-derived root apical meristem is organized around a group of infrequently dividing cells, the quiescent centre, that maintains the stem cells, organizes growth along two axes and owing to its resistance to 3ic stress can replace damaged stem cells. In most cases, lateral roots post-embryonically branch off the primary and establish a new root meristem which organization is identical to the primary root one. The cellular and molecular processes underpinning the emergence of new stem cell niches are not well known. Here, we characterize the de novo establishment of the root apical meristem in lateral roots. While the position of the new stem cell niche is set early during morphogenesis, its cellular layout, unique gene expression profile and mitotic quiescence are only acquired after emergence concomitant to the establishment of two diverging growth axis. Our results show that the intertwined attributes of the mature root stem cell niche are progressively acquired during lateral root formation, and support a model in which the position of the stem cell niche emerges from the establishment of diverging growth axis.HighlightAnalyze of the ontogeny of the quiescent center during lateral root ontogeny reveal its late formation and supports that its emergence results from the establishment of two diverging growth axis.
SpheroidAnalyseR – an online platform for analysing data from 3D spheroids or organoids grown in 96-well plates
Authors: Barrow Rhiannon , Wilkinson Joseph N , He Yichen , Callaghan Martin , Brüning-Richardson Anke , Dunning Mark , Stead Lucy F 
Published: February 2022

ABSTRACTSpheroids and organoids are increasingly popular three-dimensional (3D) cell culture models. Spheroid models are more physiologically relevant to a tumour compared to two-dimensional (2D) cultures and organoids are a simplified version of an organ with similar composition. Both can be used in cell migration studies, disease modelling and drug discovery. A drawback of these models is, however, the lack of appropriate analytical tools for high throughput imaging and analysis over a time course. To address this, we have developed an R Shiny app called SpheroidAnalyseR: a simple, fast, effective open-source app that allows the analysis of spheroid or organoid size data generated in a 96-well format. SpheroidAnalyseR processes and analyses datasets of image measurements that can be obtained via a bespoke software, described herein, that automates spheroid imaging and quantification using the Nikon A1R Confocal Laser Scanning Microscope. However, templates are provided to enable users to input spheroid image measurements obtained by user-preferred methods. SpheroidAnalyseR facilitates outlier identification and removal followed by graphical visualisation of spheroid measurements across multiple predefined parameters such as time, cell-type and treatment(s). Spheroid imaging and analysis can, thus, be reduced from hours to minutes, removing the requirement for substantial manual data manipulation in a spreadsheet application. The combination of spheroid generation in 96-well ultra-low attachment microplates, imaging using our bespoke software, and analysis using SpheroidAnalyseR toolkit allows high throughput, longitudinal quantification of 3D spheroid growth whilst minimising user input and significantly improving the efficiency and reproducibility of data analysis. Our bespoke imaging software is available from https://github.com/GliomaGenomics. SpheroidAnalyseR is available at https://spheroidanalyser7.azurewebsites.net, and the source code found at https://github.com/GliomaGenomics.Abstract FigureGraphical abstract - SpheroidAnalyseR main steps.A summary of the process followed within the SpheroidAnalyseR app. Dotted boxes are the steps required to produce the input data for SpheroidAnalyseR. Solid boxes show the 5 main steps of SpheroidAnalyseR: Data input, Preview, Outlier removal, Merging and Plotting.
An assessment of bioinformatics tools for the detection of human endogenous retroviral insertions in short-read genome sequencing data
Authors: Bowles Harry , Kabiljo Renata , Jones Ashley , Al Khleifat Ahmad , Quinn John P , Dobson Richard JB , Swanson Chad M , Al-Chalabi Ammar , Iacoangeli Alfredo 
Published: February 2022

AbstractThere is a growing interest in the study of human endogenous retroviruses (HERVs) given the substantial body of evidence that implicates them in many human diseases. Although their genomic characterization presents numerous technical challenges, next-generation sequencing (NGS) has shown potential to detect HERV insertions and their polymorphisms in humans, and a number of computational tools to detect them in short-read NGS data exist. In order to design optimal analysis pipelines, an independent evaluation of the currently available tools is required. We evaluated the performance of a set of such tools using a variety of experimental designs and types of NGS datasets. These included 50 human short read whole-genome sequencing samples, matching long and short read NGS data, and simulated short-read NGS data. Our results highlight the performance variability of the tools across the datasets and suggest that different tools might be suitable for different study designs. Using multiple tools and a consensus approach is advisable if computationally feasible and wet-lab validation via PCR is advisable where biological samples are available.
Exploring the link between Parkinson’s disease and Diabetes Mellitus in Drosophila
Authors: Sanz Francisco José , Solana-Manrique Cristina , Lilao-Garzón Joaquín , Brito-Casillas Yeray , Muñoz-Descalzo Silvia , Paricio Nuria 
Published: February 2022

ABSTRACTParkinson’s disease (PD) is the second most common neurodegenerative disease. Diabetes mellitus (DM) is a metabolic disease characterized by high levels of glucose in blood. Recent epidemiological studies are highlighting the link between both diseases; it is even considered that DM might be a risk factor for PD. To further investigate the likely relation of these diseases, we have used a Drosophila PD model based on inactivation of the DJ-1β gene (ortholog of human DJ-1), and diet-induced Drosophila and mouse T2DM models, together with human neuron-like cells. T2DM models were obtained by feeding flies with a high sugar containing medium, and mice with a high fat diet. Our results showed that both fly models exhibit common phenotypes such as alterations in carbohydrate homeostasis, mitochondrial dysfunction or motor defects, among others. In addition, we demonstrated that T2DM might be a risk factor of developing PD since our diet-induced fly and mouse T2DM models present DA neurodegeneration, a hallmark of PD. We have also confirmed that neurodegeneration is caused by increased glucose levels, which has detrimental effects in human neuron-like cells by triggering apoptosis and leading to cell death. Besides, the observed phenotypes were exacerbated in DJ-1β mutants cultured in the high sugared medium, indicating that DJ-1 might have a role in carbohydrate homeostasis. Finally, we have confirmed that metformin, an antidiabetic drug, is a potential candidate for PD treatment and that it could prevent PD onset in T2DM model flies. This result supports antidiabetic drugs as promising PD therapeutics.
Is Over-parameterization a Problem for Profile Mixture Models?
Authors: Baños Hector , Susko Edward , Roger Andrew J. 
Published: February 2022

AbstractBiochemical constraints on the admissible amino acids at specific sites in proteins leads to heterogeneity of the amino acid substitution process over sites in alignments. It is well known that phylogenetic models of protein sequence evolution that do not account for site heterogeneity are prone to long-branch attraction (LBA) artifacts. Profile mixture models were developed to model heterogeneity of preferred amino acids at sites via a finite distribution of site classes each with a distinct set of equilibrium amino acid frequencies. However, it is unknown whether the large number of parameters in such models associated with the many amino acid frequency classes can adversely affect tree topology estimates because of over-parameterization. Here we demonstrate theoretically that for long sequences, over-parameterization does not create problems for estimation with profile mixture models. Under mild conditions, tree, amino acid frequencies and other model parameters converge to true values as sequence length increases, even when there are large numbers of components in the frequency profile distributions. Because large sample theory does not necessarily imply good behavior for shorter alignments we explore performance of these models with short alignments simulated with tree topologies that are prone to LBA artifacts. We find that over-parameterization is not a problem for complex profile mixture models even when there are many amino acid frequency classes. In fact, simple models with few site classes behave poorly. Interestingly, we also found that misspecification of the amino acid frequency classes does not lead to increased LBA artifacts as long as the estimated cumulative distribution function of the amino acid frequencies at sites adequately approximates the true one. In contrast, misspecification of the amino acid exchangeability rates can severely negatively affect parameter estimation. Finally, we explore the effects of including in the profile mixture model an additional ‘F-class’ representing the overall frequencies of amino acids in the data set. Surprisingly, the F-class does not help parameter estimation significantly, and can decrease the probability of correct tree estimation, depending on the scenario, even though it tends to improve likelihood scores.
Ethanol exposure alters Alzheimer’s-related pathology, behavior, and metabolism in APP/PS1 mice
Authors: Gironda Stephen C. , Day Stephen M. , Clarke Caitlin W. , Snipes J. Andy , Nicol Noelle I. , Kamran Hana , Vaughn Warner , Macauley Shannon L. , Weiner Jeff L. 
Published: February 2022

AbstractChronic ethanol exposure can increase amyloid-β (Aβ) and tau in rodent models of Alzheimer’s-disease (AD)-like pathology, yet the underlying mechanisms are poorly understood. In this study, a moderate two-bottle choice drinking paradigm was used to identify how chronic ethanol exposure alters Aβ-related pathology, metabolism, and behavior. Complementary in vivo microdialysis experiments were used to measure how acute ethanol directly modulates Aβ in the hippocampal interstitial fluid (ISF). Ethanol-exposed APPswe/PSEN1dE9 (APP/PS1) mice showed increased brain atrophy and an increased number of amyloid plaques. Further analysis revealed that ethanol exposure led to a shift in the distribution of plaque size in the cortex and hippocampus. Ethanol-exposed mice developed a greater number of smaller plaques, potentially setting the stage for increased plaque proliferation in later life. Ethanol also induced changes in N-methyl-D-aspartate and γ-aminobutyric acid type-A receptor (NMDAR and GABAAR, respectively) expression, possibly reflecting changes in the excitatory and inhibitory (E/I) balance in the brain. Ethanol exposure also led to a diurnal shift in feeding behavior which was associated with changes in glucose homeostasis and glucose intolerance. Ethanol exposure also exacerbated alterations in the open-field test and deficits in nest-building behaviors in APP/PS1mice. Lastly, an acute dose of ethanol bidirectionally altered hippocampal ISF Aβ levels – decreasing during the initial exposure and increasing during withdrawal. Acute ethanol exposure increased hippocampal ISF glucose levels, suggesting changes in cerebral glucose metabolism occur in response to ethanol. These experiments indicate that ethanol exacerbates an AD-like phenotype by altering Aβ deposition, behavior, and metabolism. Here, even a moderate drinking paradigm culminates in an interaction between alcohol use and AD-related phenotypes with a potentiation of AD-related pathology, behavioral dysfunction, and metabolic impairment.HighlightsChronic ethanol exposure increases brain atrophy in APP/PS1 mice.Chronic ethanol exposure increased the number of plaques in the brains of APP/PS1 mice.Chronic ethanol exposure led to dysregulated metabolism in APP/PS1 mice.Chronic ethanol exposure altered anxiety- and dementia-related behaviors in APP/PS1 mice.Acute ethanol exposure bidirectionally alters interstitial fluid (ISF) levels of amyloid-β in APP/PS1 mice during exposure and withdrawal.
An increase in serial sarcomere number induced via weighted downhill running improves work loop performance in the rat soleus
Authors: Hinks Avery , Jacob Kaitlyn , Mashouri Parastoo , Medak Kyle D. , Franchi Martino V. , Wright David C. , Brown Stephen H. M. , Power Geoffrey A. 
Published: February 2022

AbstractIncreased serial sarcomere number (SSN) has been observed in rats via downhill running training due to the emphasis on active lengthening contractions; however, little is known about the influence on dynamic contractile function. Therefore, we employed 4 weeks of weighted downhill running training in rats, then assessed soleus SSN and work loop performance. We hypothesized trained rats would produce greater net work output during faster, higher-strain work loops due to a greater SSN. Thirty-one Sprague-Dawley rats were assigned to a control or training group. Weight was added during downhill running via a custom-made vest, progressing from 5-15% body mass. Following sacrifice, the soleus was dissected, and a force-length relationship was constructed. Work loops (active shortening followed by passive lengthening) were then performed about optimal muscle length (LO) at 1.5-3-Hz cycle frequencies and 1-7-mm strains to assess net work output. Muscles were then fixed in formalin at LO. Fascicle lengths and sarcomere lengths were measured and used to calculate SSN. Intramuscular collagen content and crosslinking were quantified via a hydroxyproline content and pepsin-solubility assay. Trained rats had longer fascicle lengths (+13%), greater SSN (+8%), greater specific active forces (+50%), and lower passive forces (–45-62%) than controls (P<0.05). There were no differences in collagen parameters (P>0.05). Net work output was greater (+101-424%) in trained than control rats for the 1.5-Hz loops at 1, 3, and 5-mm strains (P<0.05) and showed relationships with fascicle length (R2=0.14-0.24, P<0.05). These results suggest training-induced longitudinal muscle growth may improve dynamic performance.
Integrated epigenome and transcriptome analysis of normal and arrested meiotic initiation during mouse spermatogenesis
Authors: Zhang Xiaoyu , Gunewardena Sumedha , Wang Ning 
Published: February 2022

AbstractThe transition from mitotic to meiotic cell cycles is a transcriptional event that entails the activation of genes important for meiosis and requires germline-specific retinoic acid (RA) signaling target, Stra8. To identify novel transcription factors underlying mammalian meiotic initiation, we conducted integrative snATAC-seq and scRNA-seq analysis using wild-type and Stra8-deficient mouse testicular cells to map the chromatin accessibility and gene expression landscapes of normal and genetically arrested meiotic initiation. Our results identified a cluster of putative inhibitory transcription factors for meiotic initiation, which we consider “meiotic inhibitors”. STRA8 binds to the regulatory sequences of these meiotic inhibitors and represses their expression upon meiotic initiation. In Stra8-deficient cells that suffer meiotic initiation arrest, the chromatin accessibility of these meiotic inhibitors is increased, concurrent with their uncontrolled and sustained expression. Among these meiotic inhibitors include KLF4, MAX, and MAZ. Importantly, by analyzing the single cell transcriptomes of human testes, our data show that these putative meiotic inhibitor genes are upregulated in early germ cells from patients with spermatogenic failure. Our study suggests that proper repression of meiotic inhibitors is essential for both mouse and human spermatogenesis.
Evaluating Impacts of Syntenic Block Detection Strategies on Rearrangement Phylogeny Using M. tuberculosis Isolates
Authors: Elghraoui Afif , Mirarab Siavash , Swenson Krister M. , Valafar Faramarz 
Published: February 2022

AbstractPhylogenetic inference based on genomic structural variations, that manipulate the gene order and content of whole chromosomes, promises to inform a more comprehensive understanding of evolution. The first challenge in using such data, the incompleteness of availablede novoassemblies, is easing as long read technologies enable (near-)complete genome assembly, but methodological challenges remain. To obtain the input to rearrangement-based inference methods, we need to detect syntenic blocks of orthologous sequences, a task that can be accomplished in many ways, none of which are obviously preferable. In this paper, we use 94 reference quality genomes of primarilyMycobacterium tuberculosis(Mtb) isolates as a benchmark to evaluate these methods. The clonal nature of Mtb evolution, the manageable genome sizes, along with substantial levels of structural variation make this an ideal benchmarking dataset. We test several methods for detecting homology and obtaining syntenic blocks, and two methods for inferring phylogenies, comparing them to the standard method that uses substitutions for inferring the tree. We find that not only the choice of methods but also their parameters can impact results, especially among branches with lower support. In particular, a method based on an encoding of adjacencies applied to Cactus-defined blocks was fully compatible with the highly supported branches of the substitution-based tree. Thus, we were able tocombinethe two trees to obtain a supertree with high resolution utilizing both SNPs and rearrangements. Furthermore, we observed that the results were much less affected by the choice of the tree inference method than by the method used to determine the underlying syntenic blocks. Overall, our results indicate that accurate trees can be inferred using genome rearrangements, but the choice of the methods for inferring the homology matters and requires care.