bluuebunny/crossref_metadata_2025_split huggingface dataset:
Are we allowed to visit now? Concerns and issues surrounding vaccination and infection risks in UK care homes during COVID-19
Authors: Giebel Clarissa , Hanna Kerry , Cannon Jacqueline , Marlow Paul , Tetlow Hilary , Mason Stephen , Shenton Justine , Rajagopal Manoj , Gabbay Mark 
Published: May 2021

AbstractBackgroundVaccination uptake in the UK and increased care home testing are likely affecting care home visitation. With scant scientific evidence to date, the aim of this longitudinal qualitative study was to explore the impact of both (vaccination and testing) on the conduct and experiences of care home visits.MethodsFamily carers of care home residents with dementia and care home staff from across the UK took part in baseline (October/November 2020) and follow-up interviews (March 2021). Public advisers were involved in all elements of the research. Data were analysed using thematic analysis.ResultsAcross 62 baseline and follow-up interviews with family carers (n=26; 11) and care home staff (n=16; 9), five core themes were developed: Delayed and inconsistent offers of face-to-face visits; Procedures and facilitation of visits; Frustration and anger among family carers; Variable uptake of the COVID-19 vaccine; Misinformation, education, and free choice. The variable uptake in staff, compared to family carers, was a key factor seemingly influencing visitation, with a lack of clear guidance leading care homes to implement infection control measures and visitation rights differently.ConclusionsWe make five recommendations in this paper to enable improved care home visitation in the ongoing, and in future, pandemics. Visits need to be enabled and any changes to visiting rights must be used as a last resort, reviewed regularly in consultation with residents and carers and restored as soon as possible as a top priority, whilst more education needs to be provided surrounding vaccination for care home staff.
Dynamical Systems Modeling of Early-Term Immune Reconstitution with Different Anti-Thymocyte Globulin (ATG) Administration Schedules in Allogeneic Stem Cell Transplantation
Authors: Zelikson Viktoriya , Simmons Gary , Raman Natasha , Krieger Elizabeth , Rebiero Anatevka , Hawks Kelly , Aziz May , Roberts Catherine , Reed Jason , Gress Ronald , Toor Amir 
Published: May 2021

AbstractAlloreactivity forms the basis of allogeneic hematopoietic cell transplantation (HCT), with donor derived T cell response to recipient antigens mediating clinical responses either in part or entirely. These encompass the different manifestations of graft vs. host disease (GVHD), infection risk as well as disease response. Whilst the latter is contingent upon disease biology and thus may be less predictable, the former two are more likely to be directly proportional to the magnitude of donor derived T cell recovery. Herein we explore the quantitative aspects of immune cell recovery following allogeneic HCT and clinical outcomes in two cohorts of HLA matched allograft recipients who received rabbit anti-thymocyte globulin (ATG) on different schedules (days -9 to -7 vs. -3 to -1). Monocyte as well as donor derived T cell (ddCD3) recovery was superior in those given ATG early in their course (days -9/-7). This difference was related to a more rapid rate of ddCD3 recovery, largely driven by CD3+/8+ cells in the first month following transplantation. Early monocyte recovery was associated with later T cell recovery, improved survival, and less chronic GVHD. In contrast rapid and early ddCD3 expansion out of proportion to monocyte recovery was associated with a high likelihood of acute GVHD and poor survival. This analytic methodology demonstrates that modelling ‘early-term immune reconstitution’ following HCT yields insights that may be useful in management of post-transplant immunosuppression and adaptive cellular therapy to optimize clinical outcomes.HighlightsATG given early (day -9 to -7) prior to HCT leads to improved survival and non-relapse mortality. Improved monocyte counts as well as donor-derived T cell counts are seen in recipients of early ATG. Improved clinical outcomes are observed in patients with enhanced monocyte and T cell recovery after HCT.
Disease-specific contribution of pulvinar dysfunction to impaired emotion recognition in schizophrenia
Authors: Martínez Antígona , Tobe Russell H. , Gaspar Pablo A. , Malinsky Daniel , Dias Elisa C. , Sehatpour Pejman , Lakatos Peter , Patel Gaurav H. , Silipo Gail , Javitt Daniel C. 
Published: May 2021

AbstractOne important aspect for managing social interactions is the ability to rapidly and accurately perceive and respond to facial expressions, which is highly dependent upon intact processing within both cortical and subcortical components of the early visual pathways. Social cognitive deficits, including face emotion recognition (FER) deficits, are characteristic of several neuropsychiatric disorders, including schizophrenia (Sz) and autism spectrum disorders (ASD). Here, we investigated potential visual sensory contributions to FER deficits in Sz (n=28) and adult ASD (n=20) participants compared to neurotypical (n=30) controls using task-based fMRI during an implicit static/dynamic FER task. Compared to neurotypical controls, both Sz and ASD participants had significantly lower FER scores which interrelated with diminished activation of the superior temporal sulcus (STS). In Sz, STS deficits were predicted by reduced activation of both early visual regions and the pulvinar nucleus of the thalamus, along with impaired cortico-pulvinar interaction. By contrast, ASD participants showed patterns of increased early visual cortical and pulvinar activation. Large effect-size structural and histological abnormalities of pulvinar have previously been documented in Sz. Moreover, we have recently demonstrated impaired pulvinar activation to simple visual stimuli in Sz. Here, we provide the first demonstration of a disease-specific contribution of impaired pulvinar activation to social cognitive impairment in Sz.
M-DATA: A Statistical Approach to Jointly Analyzing De Novo Mutations for Multiple Traits
Authors: Xie Yuhan , Li Mo , Dong Weilai , Jiang Wei , Zhao Hongyu 
Published: May 2021

AbstractRecent studies have demonstrated that multiple early-onset diseases have shared risk genes, based on findings from de novo mutations (DNMs). Therefore, we may leverage information from one trait to improve statistical power to identify genes for another trait. However, there are few methods that can jointly analyze DNMs from multiple traits. In this study, we develop a framework called M-DATA (Multi-trait framework for De novo mutation Association Test with Annotations) to increase the statistical power of association analysis by integrating data from multiple correlated traits and their functional annotations. Using the number of DNMs from multiple diseases, we develop a method based on an Expectation-Maximization algorithm to both infer the degree of association between two diseases as well as to estimate the gene association probability for each disease. We apply our method to a case study of jointly analyzing data from congenital heart disease (CHD) and autism. Our method was able to identify 23 genes for CHD from joint analysis, including 12 novel genes, which is substantially more than single-trait analysis, leading to novel insights into CHD disease etiology.Author SummaryCongenital heart disease (CHD) is the most common birth defect. With the development of new generation sequencing technology, germline mutations such as de novo mutations (DNMs) with deleterious effects can be identified to aid in discovering the genetic causes for early on-set diseases such as CHD. However, the statistical power is still limited by the small sample size of DNM studies due to the high cost of recruiting and sequencing samples, and the low occurrence of DNMs given its rarity. Compared to DNM analysis for other diseases, it is even more challenging for CHD given its genetic heterogeneity. Recent research has suggested shared disease mechanisms between early-onset neurodevelopmental diseases and CHD based on findings from DNMs. Currently, there are few methods that can jointly analyze DNM data on multiple traits. Therefore, we develop a framework to identify risk genes for multiple traits simultaneously for DNM data. The new method is applied to CHD and autism as a case study to demonstrate its improved power in identifying risk genes compared with single-trait analysis. Our results lead to new insights on the disease etiology of CHD, and the shared etiological mechanisms between CHD and autism.
Theory of local k-mer selection with applications to long-read alignment
Authors: Shaw Jim , Yu Yun William 
Published: May 2021

AbstractMotivationSelecting a subset of k-mers in a string in a local manner is a common task in bioinformatics tools for speeding up computation. Arguably the most well-known and common method is the minimizer technique, which selects the ‘lowest-ordered’ k-mer in a sliding window. Recently, it has been shown that minimizers are a sub-optimal method for selecting subsets of k-mers when mutations are present. There is however a lack of understanding behind the theory of why certain methods perform well.ResultsWe first theoretically investigate the conservation metric for k-mer selection methods. We derive an exact expression for calculating the conservation of a k-mer selection method. This turns out to be tractable enough for us to prove closed-form expressions for a variety of methods, including (open and closed) syncmers, (α, b, n)-words, and an upper bound for minimizers. As a demonstration of our results, we modified the minimap2 read aligner to use a more optimal k-mer selection method and demonstrate that there is up to an 8.2% relative increase in number of mapped reads.Availability and supplementary informationSimulations and supplementary methods available at https://github.com/bluenote-1577/local-kmer-selection-results. os-minimap2 is a modified version of minimap2 and available at https://github.com/bluenote-1577/os-minimap2.Contactjshaw@math.toronto.edu
Simultaneous pure T2 and varying T2′-weighted BOLD fMRI using Echo Planar Time-resolved Imaging for mapping cortical-depth dependent responses
Authors: Wang Fuyixue , Dong Zijing , Wald Lawrence L. , Polimeni Jonathan R. , Setsompop Kawin 
Published: May 2021

AbstractSpin-echo (SE) BOLD fMRI has high microvascular specificity, and thus provides a more reliable means to localize neural activity compared to conventional gradient-echo BOLD fMRI. However, the most common SE BOLD acquisition method, SE-EPI, is known to suffer from T2′ contrast contamination with undesirable draining vein bias. To address this, in this study, we extended a recently developed distortion/blurring-free multi-shot EPI technique, Echo-Planar Time-resolved Imaging (EPTI), to cortical-depth dependent SE-fMRI at 7T to test whether it could provide purer SE BOLD contrast with minimal T2′ contamination for improved neuronal specificity. From the same acquisition, the time-resolved feature of EPTI also provides a series of asymmetric SE (ASE) images with varying T2′ weightings, and enables extraction of data equivalent to conventional SE EPI with different echo train lengths (ETLs). This allows us to systematically examine how T2′-contribution affects different SE acquisition strategies using a single dataset. A low-rank spatiotemporal subspace reconstruction was implemented for the SE-EPTI acquisition, which incorporates corrections for both shot-to-shot phase variations and dynamic B0 drifts. SE-EPTI was used in a visual task fMRI experiment to demonstrate that i) the pure SE image provided by EPTI results in the highest microvascular specificity; ii) the ASE EPTI series, with a graded introduction of T2′ weightings at time points farther away from the pure SE, show a gradual sensitivity increase along with increasing draining vein bias; iii) the longer ETL seen in conventional SE EPI acquisitions will induce more draining vein bias. Consistent results were observed across multiple subjects, demonstrating the robustness of the proposed technique for SE-BOLD fMRI with high specificity.
Rapid genome editing by CRISPR-Cas9-POLD3 fusion
Authors: Reint Ganna , Li Zhuokun , Labun Kornel , Keskitalo Salla , Soppa Inkeri , Mamia Katariina , Tölö Eero , Szymanska Monika , Meza-Zepeda Leonardo A. , Lorenz Susanne , Cieslar-Pobuda Artur , Hu Xian , Bordin Diana L. , Staerk Judith , Valen Eivind , Schmierer Bernhard , Varjosalo Markku , Taipale Jussi , Haapaniemi Emma 
Published: May 2021

AbstractPrecision CRISPR gene editing relies on the cellular homology-directed DNA repair (HDR) to introduce custom DNA sequences to target sites. The HDR editing efficiency varies between cell types and genomic sites, and the sources of this variation are incompletely understood. Here, we have studied the effect of 450 DNA repair protein - Cas9 fusions on CRISPR genome editing outcomes. We find the majority of fusions to improve precision genome editing only modestly in a locus- and cell-type specific manner. We identify Cas9-POLD3 fusion that enhances editing by speeding up the initiation of DNA repair. We conclude that while DNA repair protein fusions to Cas9 can improve HDR CRISPR editing, most need to be optimized to the particular cell type and genomic site, highlighting the diversity of factors contributing to locus-specific genome editing outcomes.
A cell-penetrant peptide blockingC9ORF72-repeat RNA nuclear export suppresses neurodegeneration
Authors: Castelli Lydia M. , Sanchez-Martinez Alvaro , Lin Ya-Hui , Upadhyay Santosh Kumar , Higginbottom Adrian , Cooper-Knock Johnathan , Gül Aytac , Walton Amy , Montmasson Claire , Cohen Rebecca , Bauer Claudia S. , De Vos Kurt J. , Azzouz Mimoun , Shaw Pamela J. , Dominguez Cyril , Ferraiuolo Laura , Whitworth Alexander J. , Hautbergue Guillaume M. 
Published: May 2021

AbstractHexanucleotide repeat expansions inC9ORF72are the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), a spectrum of incurable debilitating neurodegenerative diseases. Here, we report a novel ALS/FTD drug concept within vivoandin vitrotherapeutic activity in preclinical models of C9ORF72-ALS/FTD. Our data demonstrate that supplementation or oral administration of a cell-penetrant peptide, which competes with the SRSF1:NXF1 interaction, confers neuroprotection by inhibiting the nuclear export of pathologicalC9ORF72-repeat transcripts in various models of disease including primary neurons, patient-derived motor neurons andDrosophila. Our drug-like rationale for disrupting the nuclear export of microsatellite repeat transcripts in neurological disorders provides a promising alternative to conventional small molecule inhibitors often limited by poor blood-brain barrier penetrance.
Tripeptide loop closure: a detailed study of reconstructions based on Ramachandran distributions
Authors: O’Donnell T. , Robert C. H. , Cazals F. 
Published: May 2021

AbstractTripeptide loop closure (TLC) is a standard procedure to reconstruct protein backbone conformations, by solving a zero dimensional polynomial system yielding up to 16 solutions. In this work, we first show that multiprecision is required in a TLC solver to guarantee the existence and the accuracy of solutions. We then compare solutions yielded by the TLC solver against tripeptides from the Protein Data Bank. We show that these solutions are geometrically diverse (up to 3Å RMSD with respect to the data), and sound in terms of potential energy. Finally, we compare Ramachandran distributions of data and reconstructions for the three amino acids. The distribution of reconstructions in the second angular space (φ2,ψ2) stands out, with a rather uniform distribution leaving a central void.We anticipate that these insights, coupled to our robust implementation in the Structural Bioinformatics Library (https://sbl.inria.fr/doc/Tripeptide_loop_closure-user-manual.html), will boost the interest of TLC for structural modeling in general, and the generation of conformations of flexible loops in particular.
Interplay between receptor binding, immune escape and protein stability determines the natural selection of SARS-CoV-2 variants
Authors: Upadhyay Vaibhav , Lucas Alexandra , Panja Sudipta , Miyauchi Ryuki , Mallela Krishna M.G. 
Published: May 2021

ABSTRACTEmergence of new SARS-CoV-2 variants has raised concerns at the effectiveness of vaccines and antibody therapeutics developed against the unmutated wild-type virus. We examined the effect of 12 most commonly occurring mutations in the receptor binding domain on its expression, stability, activity, and antibody escape potential-some of the factors that may influence the natural selection of mutants. Recombinant proteins were expressed in human cells. Stability was measured using thermal denaturation melts. Activity and antibody escape potential were measured using isothermal titration calorimetry in terms of binding to ACE2 and to a neutralizing human antibody CC12.1, respectively. Our results show that variants differ in their expression levels with the two least stable variants showing lesser expression. Out of the 8 well-expressed mutants, only 2 (N501Y and K417T/E484K/N501Y) showed stronger affinity to ACE2, 4 (Y453F, S477N, T478I and S494P) have similar affinity, whereas the other 2 (K417N and E484K) have weaker affinity when compared to the wild-type. In terms of CC12.1 binding, when compared to the wild-type, 4 variants (K417N, Y453F, N501Y and K417T/E484K/N501Y) have weaker affinity, 2 (S477N and S494P) have similar affinity, and 2 (T478I and E484K) have stronger affinity. Taken together, these results indicate that multiple factors contribute towards the natural selection of variants, and all these factors need be considered to understand the evolution of the virus. In addition, since not all variants can escape a given neutralizing antibody, antibodies to treat new variants can be chosen based on the specific mutations in that variant.
Label-free three-dimensional analyses of live cells with deep-learning-based segmentation exploiting refractive index distributions
Authors: Choi Jinho , Kim Hye-Jin , Sim Gyuhyeon , Lee Sumin , Park Wei Sun , Park Jun Hyung , Kang Ha-Young , Lee Moosung , Heo Won Do , Choo Jaegul , Min Hyunseok , Park YongKeun 
Published: May 2021

AbstractVisualisations and analyses of cellular and subcellular organelles in biological cells is crucial for the study of cell biology. However, existing imaging methods require the use of exogenous labelling agents, which prevents the long-time assessments of live cells in their native states. Here we propose and experimentally demonstrate three-dimensional segmentation of subcellular organelles in unlabelled live cells, exploiting a 3D U-Net-based architecture. We present the high-precision three-dimensional segmentation of cell membrane, nucleus membrane, nucleoli, and lipid droplets of various cell types. Time-lapse analyses of dynamics of activated immune cells are also analysed using label-free segmentation.
Fine-scale heterogeneity in population density predicts wave dynamics in dengue epidemics
Authors: Romeo-Aznar Victoria , Freitas Laís Picinini , Cruz Oswaldo Gonçalves , King Aaron A , Pascual Mercedes 
Published: May 2021

AbstractThe spread of dengue and other arboviruses constitutes an expanding global health threat. The daunting heterogeneity in population distribution and movement in megacities of the developing world frustrates predictive modeling, even as its importance to disease spread is clearer than ever. Using surveillance data at fine resolution from Rio de Janeiro, we document a scale-invariant pattern in the size of successive epidemics following DENV4 emergence. This pattern emerges from the combined effect of herd immunity and seasonal transmission, and is strongly driven by variation in population density at sub-kilometer scales. It is apparent only when the landscape is stratified by population density and not by spatial proximity as has been common practice. Models that exploit this emergent simplicity should afford improved predictions of epidemic waves.
Describing small angle scattering profiles by a limited set of intensities
Authors: Grant Thomas D. 
Published: May 2021

AbstractSmall angle scattering (SAS) probes the size and shape of particles at low resolution through the analysis of the scattering of X-rays or neutrons passing through a solution of particles. One approach to extracting structural information from SAS data is the indirect Fourier transform (IFT). The IFT approach parameterizes the real space pair distribution function (P(r)) of a particle using a set of basis functions, which simultaneously determines the scattering profile (I(q)) using corresponding reciprocal space basis functions. This article presents an extension of an IFT algorithm proposed by Moore which used a trigonometric series to describe the basis functions, where the real space and reciprocal space basis functions are Fourier mates. An equation is presented relating the Moore coefficients to the intensities of the SAS profile at specific positions as well as a series of new equations that describe the size and shape parameters of a particle from this distinct set of intensity values. An analytical real space regularizer is derived to smooth the P(r) curve and ameliorate systematic deviations caused by series termination, commonly used in IFT methods though not described in Moore’s original approach, which is particularly susceptible to such effects. The algorithm is provided as a script, denss.fit_data.py, as part of the DENSS software package for SAS, which includes both command line and interactive graphical interfaces. Results of the program using experimental data show that it is as accurate, and often more accurate, than existing tools.