bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diet quality and risk and severity of COVID-19: a prospective cohort study
Authors: Merino Jordi , Joshi Amit D. , Nguyen Long H. , Leeming Emily R. , Mazidi Mohsen , Drew David A , Gibson Rachel , Graham Mark S. , Lo Chun-Han , Capdevila Joan , Murray Benjamin , Hu Christina , Selvachandran Somesh , Kwon Sohee , Ma Wenjie , Menni Cristina , Hammers Alexander , Bhupathiraju Shilpa N. , Sharma Shreela V. , Sudre Carole , Astley Christina M. , Willet Walter C. , Chavarro Jorge E. , Ourselin Sebastien , Steves Claire J. , Wolf Jonathan , Franks Paul W. , Spector Tim D. , Berry Sarah E. , Chan Andrew T. 
Published: June 2021

AbstractObjectivePoor metabolic health and certain lifestyle factors have been associated with risk and severity of coronavirus disease 2019 (COVID-19), but data for diet are lacking. We aimed to investigate the association of diet quality with risk and severity of COVID-19 and its intersection with socioeconomic deprivation.DesignWe used data from 592,571 participants of the smartphone-based COVID Symptom Study. Diet quality was assessed using a healthful plant-based diet score, which emphasizes healthy plant foods such as fruits or vegetables. Multivariable Cox models were fitted to calculate hazard ratios (HR) and 95% confidence intervals (95% CI) for COVID-19 risk and severity defined using a validated symptom-based algorithm or hospitalization with oxygen support, respectively.ResultsOver 3,886,274 person-months of follow-up, 31,815 COVID-19 cases were documented. Compared with individuals in the lowest quartile of the diet score, high diet quality was associated with lower risk of COVID-19 (HR, 0.91; 95% CI, 0.88-0.94) and severe COVID-19 (HR, 0.59; 95% CI, 0.47-0.74). The joint association of low diet quality and increased deprivation on COVID-19 risk was higher than the sum of the risk associated with each factor alone (Pinteraction=0.005). The corresponding absolute excess rate for lowest vs highest quartile of diet score was 22.5 (95% CI, 18.8-26.3) and 40.8 (95% CI, 31.7-49.8; 10,000 person-months) among persons living in areas with low and high deprivation, respectively.ConclusionsA dietary pattern characterized by healthy plant-based foods was associated with lower risk and severity of COVID-19. These association may be particularly evident among individuals living in areas with higher socioeconomic deprivation.
Mathematical and Statistical models as tools for the control of mosquito-borne diseases: The experience of Costa Rica
Authors: Vásquez Paola , Sanchez Fabio , Barboza Luis A. , García Yury E. , Calvo Juan G. , Chou Shu-Wei , Mery Gustavo 
Published: June 2021

AbstractThe modeling of infectious diseases provides valuable input for developing mitigating strategies and implementing public health interventions. This article highlights results and current research conducted in Costa Rica using mathematical, statistical, and computational tools to analyze transmission dynamics and provide quantitative information for developing mosquito-borne disease prevention/control methods and resource allocation planning.
Modules in connectomes of phase-synchronization comprise anatomically contiguous, functionally related regions
Authors: Williams N , Wang SH , Arnulfo G , Nobili L , Palva S , Palva JM 
Published: June 2021

AbstractModules in brain functional connectomes are essential to balancing segregation and integration of neuronal activity. Connectomes are the complete set of pairwise connections between brain regions. Non-invasive Electroencephalography (EEG) and Magnetoencephalography (MEG) have been used to identify modules in connectomes of phase-synchronization. However, their resolution is suboptimal because of spurious phase-synchronization due to EEG volume conduction or MEG field spread. Here, we used invasive, intracerebral recordings from stereo-electroencephalography (SEEG,N= 67), to identify modules in connectomes of phase-synchronization. To generate SEEG-based group-level connectomes affected only minimally by volume conduction, we used submillimeter accurate localization of SEEG contacts and referenced electrode contacts in cortical grey matter to their closest contacts in white matter. Combining community detection methods with consensus clustering, we found that the connectomes of phase-synchronization were characterized by distinct and stable modules at multiple spatial scales, across frequencies from 3 to 320 Hz. These modules were highly similar within canonical frequency bands. Unlike the distributed brain systems identified with functional Magnetic Resonance Imaging (fMRI), modules up to the high-gamma frequency band comprised only anatomically contiguous regions. Notably, the identified modules comprised cortical regions involved in shared repertoires of sensorimotor and cognitive functions including memory, language and attention. These results suggest that the identified modules represent functionally specialised brain systems, which only partially overlap with the brain systems reported with fMRI. Hence, these modules might regulate the balance between functional segregation and functional integration through phase-synchronization.HighlightsLarge-cohort SEEG used for phase-synchronization connectomicsConnectomes of phase-synchronization possess distinct and stable modulesModules in connectomes are highly similar within canonical frequency bandsModules in connectomes comprise anatomically contiguous regionsModules in connectomes comprise functionally related regions
Engineered human induced pluripotent cells enable genetic code expansion in brain organoids
Authors: van Husen Lea S. , Katsori Anna-Maria , Meineke Birthe , Tjernberg Lars O. , Schedin-Weiss Sophia , Elsässer Simon J. 
Published: June 2021

AbstractHuman induced pluripotent stem cell (hiPSC) technology has revolutionized human biology. A wide range of cell types and tissue models can be derived from hiPSCs to study complex human diseases. Here, we use PiggyBac mediated transgenesis to engineer hiPSCs with an expanded genetic code. We demonstrate that genomic integration of expression cassettes for a pyrrolysyl-tRNA synthetase (PylRS), pyrrolysyl-tRNA (PylT) and the target protein of interest enables site-specific incorporation of a non-canonical amino acid (ncAA) in response to amber stop codons. Neural stem cells, neurons and brain organoids derived from the engineered hiPSCs continue to express the amber suppression machinery and produce ncAA-bearing reporter. The incorporated ncAA can serve as a minimal bioorthogonal handle for further modifications by labeling with fluorescent dyes. Site-directed ncAA mutagenesis will open a wide range of applications to probe and manipulate proteins in brain organoids and other hiPSC-derived cell types and complex tissue models.TOC
Application of a convolutional neural network to the quality control of MRI defacing
Authors: Delbarre Daniel J. , Santos Luis , Ganjgahi Habib , Horner Neil , McCoy Aaron , Westerberg Henrik , Häring Dieter A. , Nichols Thomas E. , Mallon Ann-Marie 
Published: June 2021

AbstractLarge-scale neuroimaging datasets present unique challenges for automated processing pipelines. Mo-tivated by a large clinical trials dataset of Multiple Sclerosis with over 235,000 MRI scans, we consider the challenge of defacing - anonymisation to remove identifying facial features. The defacing process must undergo quality control (QC) checks to ensure that the facial features have been adequately anonymised and that the brain tissue is left completely intact. Visual QC checks – particularly on a project of this scale – are time-consuming and can cause delays in preparing data. We have developed a convolutional neural network (CNN) that can assist with the QC of the application of MRI defacing; our CNN is able to distinguish between scans that are correctly defaced, and can also classify defacing failures into three sub-types to facilitate parameter tuning during remedial re-defacing. Since integrating the CNN into our anonymisation pipeline, over 75,000 scans have been processed. Strict thresholds have been applied so that ambiguous classifications are referred for visual QC checks, however all scans still undergo a time-efficient verification check before being marked as passed. After applying the thresholds, our network is 92% accurate and is able to classify nearly half of the scans without the need for protracted manual checks. Even with the introduction of the verification checks, incorporation of the CNN has reduced the time spent undertaking QC checks by 42% during initial defacing, and by 35% overall. With the help of the CNN, we have been able to successfully deface 96% of the scans in the project whilst maintaining high QC standards. In a similarly sized new project of this scale, we would expect the model to reduce the time spent on manual QC checks by 125 hours. Our approach is applicable to other projects with the potential to greatly improve the efficiency of imaging anonymisation pipelines.
The Forget-Me-Not dHCP study: 7 Tesla high resolution diffusion imaging in the unfixed post-mortem neonatal brain
Authors: Wu Wenchuan , Baxter Luke , Rieger Sebastian W , Adams Eleri , Andersson Jesper LR , Andrade Maria Cobo , Andritsou Foteini , Bastiani Matteo , Fry Ria Evans , Frost Robert , Fitzgibbon Sean , Foxley Sean , Fowler Darren , Gallagher Chris , Howard Amy FD , Hajnal Joseph V , Moultrie Fiona , Monk Vaneesha , Porter David Andrew , Papp Daniel , Price Anthony , Sallet Jerome , Sanders Michael , Wilkinson Dominic , Smith Stephen M , Slater Rebeccah , Miller Karla L 
Published: June 2021

AbstractDiffusion MRI of the neonatal brain allows investigation of the organisational structure of maturing fibres during brain development. Post-mortem imaging has the potential to achieve high resolution by using long scan times, enabling precise assessment of small structures. The Forget-Me-Not study, part of the Developing Human Connectome Project (dHCP), aims to acquire and publicly distribute high-resolution diffusion MRI data for unfixed post-mortem neonatal brain at 7T with a custom-built head coil. This paper describes how the study addressed logistical, technical and ethical challenges relating to recruitment pipeline, care pathway, tissue preservation, scan setup and protocol optimisation. Results from the first subject recruited to the study demonstrate high-quality diffusion MRI data. Preliminary voxel-wise and tractography-based analyses are presented for the cortical plate, subplate and white matter pathways, with comparison to age-matched in vivo dHCP data. These results demonstrate that high quality post-mortem data can be acquired and provide a sensitive means to explore the developing human brain, as well as altered diffusion properties consistent with post-mortem changes, at high resolution.
High viral abundance and low diversity are associated with increased CRISPR-Cas prevalence across microbial ecosystems
Authors: Meaden S. , Biswas A. , Arkhipova K. , Morales S. E. , Dutilh B. E. , Westra E. R. , Fineran P. C. 
Published: June 2021

AbstractCRISPR-Cas are adaptive immune systems that protect their hosts against viruses and other parasitic mobile genetic elements. Consequently, selection from viruses and other genetic parasites is often assumed to drive the acquisition and maintenance of these immune systems in nature, but this remains untested. Here, we analyse the abundance of CRISPR arrays in natural environments using metagenomic datasets from 332 terrestrial, aquatic and host-associated ecosystems. For each metagenome we quantified viral abundance and levels of viral community diversity to test whether these variables can explain variation in CRISPR-Cas abundance across ecosystems. We find a strong positive correlation between CRISPR-Cas abundance and viral abundance. In addition, when controlling for differences in viral abundance, we found that the CRISPR-Cas systems are more abundant when viral diversity is low. We also found differences in relative CRISPR-Cas abundance among environments, with environmental classification explaining ∼24% of variation in CRISPR-Cas abundance. However, the correlations with viral abundance and diversity are broadly consistent across diverse natural environments. These results indicate that viral abundance and diversity are major ecological factors that drive the selection and maintenance of CRISPR-Cas in microbial ecosystems.Significance statementNumerous studies demonstrate that CRISPR-Cas immune systems can provide defence against bacteriophage and archaeal viruses, yet little is known about the ecological conditions where CRISPR-Cas immunity is favoured. Moreover, our knowledge is largely confined to laboratory studies and it is unknown if viruses are a key selective driver of CRISPR-Cas in nature. Using metagenomic data from diverse environments we find that both viral abundance and the abundance of CRISPR-Cas immune systems correlate positively across most environments. Furthermore, CRISPR-Cas systems are more prevalent when viral diversity is low. These results extend previous theoretical work by demonstrating that viruses are a key driver of selection of CRISPR-Cas immune systems across many natural ecosystems.
Conformational changes in Lassa virus L protein associated with promoter binding and RNA synthesis activity
Authors: Kouba Tomas , Vogel Dominik , Thorkelsson Sigurdur R. , Quemin Emmanuelle R. J. , Williams Harry M. , Milewski Morlin , Busch Carola , Günther Stephan , Grünewald Kay , Rosenthal Maria , Cusack Stephen 
Published: June 2021

AbstractLassa virus, which causes annual outbreaks in West Africa with increasing case numbers in recent years, is recognized by the WHO R&D blueprint as a significant threat for public health with high epidemic potential and no effective countermeasures. The viral large (L) protein, which contains the RNA-dependent RNA polymerase, is a key player for transcription of viral mRNA and genome replication. Here we present nine cryo-EM structures of Lassa virus L protein in the apo-, promoter-bound pre-initiation and active RNA synthesis states. We characterize distinct binding pockets for the conserved genomic 3’ and 5’ promoter RNAs and show how full-promoter binding induces a distinct pre-initiation conformation. In the apo- and elongation states, the endonuclease is inhibited by the binding of two distinct L protein peptides in the active site, respectively, whereas in the pre-initiation state, the endonuclease is uninhibited. In the stalled, early elongation state, a template-product duplex is bound in the active site cavity together with an incoming non-hydrolysable nucleotide. In this configuration, the full C-terminal region of the L protein, including the putative cap-binding domain, is highly ordered. The structural data are complemented by in vitro and cell-based studies testing a broad range of L protein mutants to probe functional relevance. These data advance our mechanistic understanding of how this flexible and multifunctional molecular machine is activated and will underpin antiviral drug development targeting the arenavirus L protein.
AI for predicting chemical-effect associations at the chemical universe level – deepFPlearn
Authors: Schor Jana , Scheibe Patrick , Bernt Matthias , Busch Wibke , Lai Chih , Hackermüller Jörg 
Published: June 2021

AbstractMany chemicals are out there in our environment, and all living species are exposed. However, numerous chemicals pose risks, such as developing severe diseases, if they occur at the wrong time in the wrong place. For the majority of the chemicals, these risks are not known. Chemical risk assessment and subsequent regulation of use require efficient and systematic strategies. Lab-based methods – even if high throughput – are too slow to keep up with the pace of chemical innovation. Existing computational approaches are designed for specific chemical classes or sub-problems but not usable on a large scale. Further, the application range of these approaches is limited by the low amount of available labeled training data.We present the ready-to-use and stand-alone program deepFPlearn that predicts the association between chemical structures and effects on the gene/pathway level using a combined deep learning approach. deepFPlearn uses a deep autoencoder for feature reduction before training a deep feedforward neural network to predict the target association. We received good prediction qualities and showed that our feature compression preserves relevant chemical structural information. Using a vast chemical inventory (unlabeled data) as input for the autoencoder did not reduce our prediction quality but allowed capturing a much more comprehensive range of chemical structures. We predict meaningful - experimentally verified-associations of chemicals and effects on unseen data. deepFPlearn classifies hundreds of thousands of chemicals in seconds.We provide deepFPlearn as an open-source and flexible tool that can be easily retrained and customized to different application settings at https://github.com/yigbt/deepFPlearn.Supplementary informationSupplementary data are available at bioRxiv online.Contactjana.schor@ufz.de
Isolation and characterizations of a novel H6N1 avian influenza virus from Von Schrenck’s Bittern (Ixobrychus eurhythmus) in Jiangxi province, China
Authors: Attaran Hamidreza , Jin Wen , Luo Jing , Wang Chengmin , He Hongxuan 
Published: June 2021

AbstractIn June 2013, the first case of human infection with an avian H6N1 virus was reported in a Taiwanese woman. Although this was a single non-fatal case, the virus continues to circulate in Taiwanese poultry. As with any emerging avian virus that infects humans, there is concern that acquisition of human-type receptor specificity could enable transmission in the human population. Despite mutations in the receptor-binding pocket of the human H6N1 isolate, it has retained avian-type (NeuAca2-3Gal) receptor specificity.An H6N1 AIV was isolated from a Von Schrenck’s Bittern during national active surveillance project for avian influenza viruses (AIVs) in wild birds in Jiangxi province, China 2018. Phylogenetic analysis showed that this strain received its genes from H1, H2, H3, H4, H6 and H10 AIVs in different places. This strain was found to be minimally pathogenic in mice and was able to replicate in mice without prior adaptation. Considering that the reassorted H6N1 virus was isolated from Von Schrenck’s Bittern in this study, it is possible that this bird can play an important role in the generation of novel reassorted H6 AIVs.In this study, H6N1 virus is a wild virus migration brought from different regions of the AIV gene into the natural gene pool, resulting in the production of a recombinant new virus. The H6N1 virus can be seen as a link in the evolution of the virus and the evolution of other viruses.
In planta genome editing with CRISPR/Cas9 ribonucleoproteins
Authors: Kumagai Yuya , Liu Yuelin , Hamada Haruyasu , Luo Weifeng , Zhu Jianghui , Kuroki Misa , Nagira Yozo , Taoka Naoaki , Kato Etsuko , Imai Ryozo 
Published: June 2021

AbstractIn planta genome editing represents an attractive approach to engineering crops/varieties that are recalcitrant to culture-based transformation methods. Here, we report the direct delivery of CRISPR/Cas9 ribonucleoproteins into the shoot apical meristem using in planta particle bombardment and introduction of a semidwarf1 (sd1)-orthologous mutation into wheat. The triple knockout tasd1 mutant of an elite wheat variety reduced culm length by 10% without a reduction in yield.
Similar neural networks respond to coherence during comprehension and production of discourse
Authors: Morales Matías , Patel Tanvi , Tamm Andres , Pickering Martin J. , Hoffman Paul 
Published: June 2021

AbstractWhen comprehending discourse, listeners engage default mode regions associated with integrative semantic processing to construct a situation model of its content. We investigated how similar networks are engaged when we produce, as well as comprehend, discourse. During fMRI, participants spoke about a series of specific topics and listened to discourse on other topics. We tested how activation was predicted by natural fluctuations in the global coherence of the discourse, i.e., the degree to which utterances conformed to the expected topic. The neural correlates of coherence were similar across speaking and listening, particularly in default mode regions. This network showed greater activation when less coherent speech was heard or produced, reflecting updating of mental representations when discourse did not conform to the expected topic. In contrast, regions that exert control over semantic activation showed task-specific effects, correlating negatively with coherence during listening but not during production. Participants who showed greater activation in left inferior prefrontal cortex also produced more coherent discourse, suggesting a specific role for this region in goal-directed regulation of speech content. Results suggest strong correspondence of discourse representations during speaking and listening. However, they indicate that the semantic control network plays different roles in comprehension and production.
Human gut Bacteroides uniformis utilizes mixed linked β- glucans via an alternative strategy
Authors: Singh Ravindra Pal , Thakur Raksha , Kumar Gulshan 
Published: June 2021

AbstractHuman gut microbial communities have a tremendous impact on well-being of the human health by producing myriad of metabolites. Polysaccharide utilizing capability of these microbial communities is a key driving force in shaping the composition of gut microbiota. Previous studies suggest that genes responsible for β- glucans utilizing in Bacteroides are present in a polysaccharide utilization locus (PUL). However, recent observations show that Bacteroides uniformis lacks such PUL archetypal organisation for efficient utilization of pustulan (β1-6) and mixed linkage (β1-4/ β1-3) glucans, and its mechanism is yet to be studied. Here, we first used BuGH16 for production of important two mixed linked β- glucan-oligosaccharides, and then demonstrate kinetics of the BuGH3MLG. The B. uniformis JCM13288T coordinates between PUL associated glycoside hydrolase (GH)-16 and distantly localised bespoke GH 3 (BuGH3MLG) for efficient utilization of mixed linkage (β1-4/ β1-3) glucans. BuGH3MLG found to be cleaved β1-4, β1-3 and β1-6 glucan-oligosaccharides. Such understanding of glycan utilization mechanism of human gut bacterial communities is crucial for development of nutraceutical therapy and improving health of human being.
Ectosomes and exosomes are distinct proteomic entities that modulate spontaneous activity in neuronal cells
Authors: Brás Inês Caldeira , Khani Mohammad Hossein , Riedel Dietmar , Parfentev Iwan , Gerhardt Ellen , Christoph van Riesen  , Urlaub Henning , Gollisch Tim , Outeiro Tiago Fleming 
Published: June 2021

SummaryExtracellular vesicles (EVs) are important mediators in intercellular communication. However, understanding the biological origin and functional effects of EVs subtypes has been challenging due to the moderate differences in their physical properties and absence of reliable markers. Here, we characterize the proteomes of ectosomes and exosomes using an improved differential ultracentrifugation protocol and quantitative proteomics. Cytoskeleton and glycolytic proteins are distinctively present in ectosomes, while endosomal sorting complexes proteins and tetraspanins are enriched in exosomes. Furthermore, annexin-A2 was identified as a specific marker for ectosomes derived from cell media and human cerebrospinal fluid. Expression of EGFP as a cytosolic reporter leads to its incorporation in EVs and enables their imaging with higher resolution. Importantly, ectosomes and exosomes internalization in neuronal cells results in the modulation of neuronal spontaneous activity. Our findings suggest that EVs cargoes reflect core intracellular processes, and their functional properties might regulate basic biological and pathological processes.