bluuebunny/crossref_metadata_2025_split huggingface dataset:
The COVID in the Context of Pregnancy, Infancy and Parenting (CoCoPIP) Study: protocol for a longitudinal study of parental mental health, social interactions, physical growth, and cognitive development of infants during the pandemic
Authors: Aydin Ezra , Weiss Staci M. , Glasgow Kevin A. , Barlow Jane , Austin Topun , Johnson Mark H. , Lloyd-Fox Sarah 
Published: May 2021

ABSTRACTIntroductionWhile the secondary impact of the COVID pandemic on the psychological wellbeing of pregnant women and parents has become apparent over the past year, the impact of these changes on early social interactions, physical growth and cognitive development of their infants is unknown, as is the way in which a range of COVID related changes have mediated this impact. This study (CoCoPIP) will investigate: i) how parent’s experiences of the social, medical, and financial changes during the pandemic have impacted pre and postnatal parental mental health and parent-infant social interaction; and (ii) the extent to which these COVID-related changes in parental pre and postnatal mental health and social interaction are associated with fetal and infant development.Methods and analysisThe CoCoPIP study is a national online survey initiated in July 2020. This ongoing study (n = 1700 families currently enrolled as of 6th May 2021) involves both quantitative and qualitative data being collected across pregnancy and infancy. It is designed to identify the longitudinal impact of the pandemic from pregnancy to two years of age, with the aim of identifying if stress-associated moderators (i.e., loss of income, COVID-19 illness, access to ante/postnatal support) impact parental mental health, and in turn, infant development. In addition, we aim to document individual differences in social and cognitive development in toddlers who were born during restrictions intended to mitigate COVID-19 spread (e.g., social distancing, national lockdowns).Ethics and disseminationEthical approval was given by the University of Cambridge, Psychology Research Ethics Committee (PREC) (PRE.2020.077). Findings will be made available via community engagement, public forums (e.g., social media,) and to national (e.g., NHS England) and local (Cambridge Universities Hospitals NHS Foundation Trust) healthcare partners. Results will be submitted for publication in peer-reviews journals.Strengths and Limitations of this study‐This is a new cohort of families being followed from prenatal to postnatal (up to 18 months) during the COVID-19 pandemic.‐The study involves the collection of quantifiable data to identify the short- and long-term influences of the pandemic on key aspects of infant development.‐The study also has a range of open-ended questions for qualitative analysis aimed at exploring familial experiences in more detail.‐The data is being collected online and is therefore limited to self- and parent-report measures, with no direct assessment of child development and parental mental health.‐Although the sample of families being recruited are diverse in their indices of multiple deprivation (IMD) and geographic location, they may not be fully representative of the wider population.
Effectiveness of COVID-19 vaccines against the B.1.617.2 variant
Authors: Bernal Jamie Lopez , Andrews Nick , Gower Charlotte , Gallagher Eileen , Simmons Ruth , Thelwall Simon , Stowe Julia , Tessier Elise , Groves Natalie , Dabrera Gavin , Myers Richard , Campbell Colin , Amirthalingam Gayatri , Edmunds Matt , Zambon Maria , Brown Kevin , Hopkins Susan , Chand Meera , Ramsay Mary 
Published: May 2021

AbstractBackgroundThe B.1.617.2 COVID-19 variant has contributed to the surge in cases in India and has now been detected across the globe, including a notable increase in cases in the UK. We estimate the effectiveness of the BNT162b2 and ChAdOx1 COVID-19 vaccines against this variant.MethodsA test negative case control design was used to estimate the effectiveness of vaccination against symptomatic disease with both variants over the period that B.1.617.2 began circulating with cases identified based on sequencing and S-gene target status. Data on all symptomatic sequenced cases of COVID-19 in England was used to estimate the proportion of cases with B.1.617.2 compared to the predominant strain (B.1.1.7) by vaccination status.ResultsEffectiveness was notably lower after 1 dose of vaccine with B.1.617.2 cases 33.5% (95%CI: 20.6 to 44.3) compared to B.1.1.7 cases 51.1% (95%CI: 47.3 to 54.7) with similar results for both vaccines. With BNT162b2 2 dose effectiveness reduced from 93.4% (95%CI: 90.4 to 95.5) with B.1.1.7 to 87.9% (95%CI: 78.2 to 93.2) with B.1.617.2. With ChAdOx1 2 dose effectiveness reduced from 66.1% (95% CI: 54.0 to 75.0) with B.1.1.7 to 59.8% (95%CI: 28.9 to 77.3) with B.1.617.2. Sequenced cases detected after 1 or 2 doses of vaccination had a higher odds of infection with B.1.617.2 compared to unvaccinated cases (OR 1.40; 95%CI: 1.13-1.75).ConclusionsAfter 2 doses of either vaccine there were only modest differences in vaccine effectiveness with the B.1.617.2 variant. Absolute differences in vaccine effectiveness were more marked with dose 1. This would support maximising vaccine uptake with two doses among vulnerable groups.
Computing Minimal Boolean Models of Gene Regulatory Networks
Authors: Karlebach Guy , Robinson Peter N 
Published: May 2021

AbstractModels of Gene Regulatory Networks (GRNs) capture the dynamics of the regulatory processes that occur within the cell as a means to understand the variability observed in gene expression between different conditions. Arguably the simplest mathematical construct used for modeling is the Boolean network, which dictates a set of logical rules for transition between states described as Boolean vectors. Due to the complexity of gene regulation and the limitations of experimental technologies, in most cases knowledge about regulatory interactions and Boolean states is partial. In addition, the logical rules themselves are not known a-priori. Our goal in this work is to create an algorithm that finds the network that fits the data optimally, and identify the network states that correspond to the noise-free data. We present a novel methodology for integrating experimental data and performing a search for the optimal consistent structure via optimization of a linear objective function under a set of linear constraints. In addition, we extend our methodology into a heuristic that alleviates the computational complexity of the problem for datasets that are generated by single-cell RNA-Sequencing(scRNA-Seq). We demonstrate the effectiveness of these tools using a public scRNA-Seq dataset and the GRN that is associated with it. Our methodology will enable researchers to obtain a better understanding of the dynamics of gene regulatory networks and their biological role.
Differential ADAR editing landscapes in major depressive disorder and suicide
Authors: Plonski Noel-Marie , Meindl Richard , Piontkivska Helen 
Published: May 2021

AbstractNeuropsychiatric disorders, including depression and suicide, are becoming an increasing public health concern. Rising rates of both depression and suicide, exacerbated by the current COVID19 pandemic, have only hastened our need for objective and reliable diagnostic biomarkers. These can aide clinicians treating depressive disorders in both diagnosing and developing treatment plans. While differential gene expression analysis has highlighted the serotonin signaling cascade among other critical neurotransmitter pathways to underly the pathology of depression and suicide, the biological mechanisms remain elusive. Here we propose a novel approach to better understand molecular underpinnings of neuropsychiatric disorders by examining patterns of differential RNA editing by adenosine deaminases acting on RNA (ADARs). We take advantage of publicly available RNA-seq datasets to map ADAR editing landscapes in a global gene-centric view. We use a unique combination of Guttman scaling and random forest classification modeling to create, describe and compare ADAR editing profiles focusing on both spatial and biological sex differences. We use a subset of experimentally confirmed ADAR editing sites located in known protein coding regions, the excitome, to map ADAR editing profiles in Major Depressive Disorder (MDD) and suicide. Using Guttman scaling, we were able to describe significant changes in editing profiles across brain regions in males and females with respect to cause of death (COD) and MDD diagnosis. The spatial distribution of editing sites may provide insight into biological mechanisms under-pinning clinical symptoms associated with MDD and suicidal behavior. Additionally, we use random forest modeling including these differential profiles among other markers of global editing patterns in order to highlight potential biomarkers that offer insights into molecular changes underlying synaptic plasticity. Together, these models identify potential prognostic, diagnostic and therapeutic biomarkers for MDD diagnosis and/or suicide.
DIRECT DETECTION OF LISTERIA MONOCYTOGENES BY RECOMBINASE POLYMERASE AMPLIFICATION
Authors: Tran Hau Thi , Tran Diem Hong , Pham Trang Nguyen Minh , Phung Huong Thi Thu 
Published: May 2021

ABSTRACTListeria monocytogenes is one of the most common types of food poisoning bacteria which can cause serious foodborne diseases or even lethality. Generally, L. monocytogenes can be detected using traditional microbiology or molecular biology techniques, notably PCR. However, the application of these methods at the field is restricted due to the strict requirement of equipment and skilled personnel. In this study, recombinase polymerase amplification (RPA), an isothermal PCR assay was developed to rapidly detect L. monocytogenes in the crude samples. The results showed that the RPA reaction, without requiring complex thermal cycles, was well-performed in the optimal conditions of 39°C within only 25 minutes. The limit of detection was identified as 310 fg of L. monocytogenes genomic DNA, which was 1000-fold more sensitive than the conventional PCR. In addition, RPA also succeeded to directly detect L. monocytogenes cells at a concentration as low as 2.5 × 101 Colony Forming Unit (CFU)/ml in pure cultures and 2.5 × 102 CFU/ml in crude samples without sample extraction or processing. Therefore, RPA established in this study could be an alternative standard method to confirm the presence of L. monocytogenes in food. Accordingly, this rapid and sensitive method could be further applied to clinical testing for the diagnosis of L. monocytogenes infection, especially in areas with limited settings.
TRIM25 and ZAP target the Ebola virus ribonucleoprotein complex to mediate interferon-induced restriction
Authors: Galão Rui Pedro , Wilson Harry , Schierhorn Kristina L , Debeljak Franka , Bodmer Bianca S , Goldhill Daniel , Hoenen Thomas , Wilson Sam J , Swanson Chad M , Neil Stuart J D 
Published: May 2021

SummaryEbola virus (EBOV) causes highly pathogenic disease in primates. Through screening a library of human interferon-stimulated genes (ISGs), we identified TRIM25 as a potent inhibitor of EBOV transcription-and-replication-competent virus-like particle (trVLP) propagation. TRIM25 overexpression inhibited the accumulation of viral genomic and messenger RNAs independently of the RNA sensor RIG-I or secondary proinflammatory gene expression. Deletion of TRIM25 strongly attenuated the sensitivity of trVLPs to inhibition by type-I interferon. The antiviral activity of TRIM25 required ZAP and the effect of type-I interferon was modulated by the CpG dinucleotide content of the viral genome. We find that TRIM25 interacts with the EBOV vRNP, resulting in its autoubiquitination and ubiquitination of the viral nucleoprotein (NP). TRIM25 is recruited to incoming vRNPs shortly after cell entry, and leads to dissociation of NP from the vRNA. We propose that TRIM25 targets the EBOV vRNP, exposing CpG-rich viral RNA species to restriction by ZAP.HighlightsTRIM25 and ZAP play a major role on type I IFN-mediated inhibition of EBOV trVLP replicationTRIM25 interacts with the EBOV NP and is recruited to vRNPs in the cytoplasm after viral entryTRIM25 ubiquitinates NP and displaces it from the viral genome, facilitating ZAP interactionZAP targets CpGs in the EBOV genome to inhibit EBOV trVLP replication
RNase E endonuclease activity and its inhibition by pseudoridine
Authors: Islam Md. Saiful , Bandyra Katarzyna J. , Chao Yanjie , Vogel Jörg , Luisi Ben F. 
Published: May 2021

AbstractThe conserved endoribonuclease RNase E dominates the dynamic landscape of RNA metabolism and underpins control mediated by small regulatory RNAs in diverse bacterial species. We explored the enzyme’s hydrolytic mechanism, allosteric activation, and interplay with partner proteins in the multi-component RNA degradosome assembly. RNase E cleaves single-stranded RNA with preference to attack the phosphate located at the 5□ nucleotide preceding uracil, and we corroborate key interactions that select that base. Unexpectedly, RNase E activity is impeded strongly when the recognised uracil is isomerised to 5-ribosyluracil (pseudouridine), from which we infer the detailed geometry of the hydrolytic attack process. Kinetics analyses support models for recognition of secondary structure in substrates by RNase E and for allosteric auto-regulation. The catalytic power of the enzyme is boosted when it is assembled into the multi-enzyme RNA degradosome, most likely as a consequence of substrate channeling. Our results rationalize the origins of substrate preferences of RNase E and illuminate its catalytic mechanism, supporting the roles of allosteric domain closure and cooperation with other components of the RNA degradosome complex.
Hidden multivalency in phosphatase recruitment by a disordered AKAP scaffold
Authors: Watson Matthew , Almeida Teresa B. , Ray Arundhati , Hanack Christina , Elston Rory , Btesh Joan , McNaughton Peter A. , Stott Katherine 
Published: May 2021

AbstractDisordered scaffold proteins provide multivalent landing pads that, via a series of embedded Short Linear Motifs (SLiMs), bring together the components of a complex to orchestrate precise spatial and temporal regulation of cellular processes. One such protein is AKAP5, which contains SLiMs that anchor PKA and Calcineurin, and recruit substrate (the TRPV1 receptor). Calcineurin is anchored to AKAP5 by a well-characterised PxIxIT SLiM. Here we show, using a combination of biochemical and biophysical approaches, that the Calcineurin PxIxIT-binding groove also recognises several hitherto unknown lower-affinity SLiMs in addition to the PxIxIT motif. We demonstrate that the assembly is in reality a complex system with conserved SLiMs spanning a wide affinity range. The capture is analogous to that seen for many DNA-binding proteins that have a weak non-specific affinity for DNA outside the canonical binding site, but different in that it involves (i) two proteins, and (ii) hydrophobic rather than electrostatic interactions. It is also compatible with the requirement for both stable anchoring of the enzyme and responsive downstream signalling. We conclude that the AKAP5 C-terminus is enriched in lower-affinity/mini-SLiMs that, together with the canonical SLiM, maintain a structurally disordered but tightly regulated signalosome.
Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification
Authors: Kanduri Chakravarthi , Pavlović Milena , Scheffer Lonneke , Motwani Keshav , Chernigovskaya Maria , Greiff Victor , Sandve Geir K. 
Published: May 2021

AbstractBackgroundMachine learning (ML) methodology development for classification of immune states in adaptive immune receptor repertoires (AIRR) has seen a recent surge of interest. However, so far, there does not exist a systematic evaluation of scenarios where classical ML methods (such as penalized logistic regression) already perform adequately for AIRR classification. This hinders investigative reorientation to those scenarios where further method development of more sophisticated ML approaches may be required.ResultsTo identify those scenarios where a baseline method is able to perform well for AIRR classification, we generated a collection of synthetic benchmark datasets encompassing a wide range of dataset architecture-associated and immune state-associated sequence pattern (signal) complexity. We trained ≈1300 ML models with varying assumptions regarding immune signal on≈850 datasets with a total of ≈210’000 repertoires containing ≈42 billion TCRβ CDR3 amino acid sequences, thereby surpassing the sample sizes of current state-of-the-art AIRR ML setups by two orders of magnitude. We found that L1-penalized logistic regression achieved high prediction accuracy even when the immune signal occurs only in 1 out of 50’000 AIR sequences.ConclusionsWe provide a reference benchmark to guide new AIRR ML classification methodology by: (i) identifying those scenarios characterised by immune signal and dataset complexity, where baseline methods already achieve high prediction accuracy and (ii) facilitating realistic expectations of the performance of AIRR ML models given training dataset properties and assumptions. Our study serves as a template for defining specialized AIRR benchmark datasets for comprehensive benchmarking of AIRR ML methods.
Microbial community structure in rice, crops, and pastures rotation systems with different intensification levels in the temperate region of Uruguay
Authors: Martínez Sebastián 
Published: May 2021

AbstractRice is an important crop in Uruguay associated mostly with livestock production in a rice and pasture rotation system since the 1920s. However, in recent years there has been interest in intensifying the production in some of these systems to satisfy market demands and increase income. Intensification occurs by augmenting the rice frequency in the rotation, including new crops like sorghum and soybean, or shortening the pasture phase. A long-term experiment was established in 2012 in the main rice producing area of Uruguay with the objective to study the impact of intensification in rice rotations. After the first cycle of rotation soils from seven rotation phases were sampled and microbial communities were studied by means of high-throughput sequencing of Illumina NovaSeq 6000. Archaeal/bacterial and fungal community composition were studied (16S rRNA and 18S gene regions) detecting 3662 and 807 bacterial and fungal Operational Taxonomic Units (OTUs), respectively.Actinobacteria,FirmicutesandProteobacteriawere the most common bacterial phyla. Among them, onlyProteobacteriadiffered significantly between rotations. Although most fungal OTUs were unidentified,Ascomycota,BasidiomycotaandMucoromycotawere the most abundant fungal classes within identified taxa. Bacterial communities differed between rotations forming three groups according to the percentage of rice in the system. Fungal communities clustered in four groups, although not well differentiated, and mostly associated with the antecessor crop. Only P and C:N varied between rotations among soil physicochemical variables after six years, and individual bacterial OTUs appeared weakly influenced by P, pH, Mg and fungal OTUs by P. The results suggest that after six years, bacteria/archaeal communities were influenced by the time with rice in the rotation, and fungal communities were more influenced by the antecessor crop. More studies are needed to associate fungal communities with certain rotational or environmental variables. Some taxa were associated with a particular rotation, and some bacterial taxa were identified as biomarkers. Fungal indicator taxa were not identified at the species level for any rotation.
P53 is a direct regulator of the immune co-stimulatory molecule CD80
Authors: Alibo Eziwoma , Mollaoglu Gurkan , Dhainaut Maxime , Zhao Royce , Rose Samuel , Baccarini Alessia , Parsons Ramon , Brown Brian D. 
Published: May 2021

SUMMARYIncreasing evidence indicates oncogenes and tumor suppressors not only influence cell fitness but can also control the immunophenotype of cells. Here, we examined how 34 commonly mutated genes in colorectal cancer (CRC) may influence the expression of 8 key immunomodulatory proteins. To do this, we employed a functional genomics approach utilizing Pro-Code/CRISPR libraries for high-dimensional analysis. We introduced a library of 102 Pro-Code/gRNA combinations, targeting each of the 34 genes, in CT26 cells, a CRC cell model, and measured the expression of each of the immunomodulatory proteins by CyTOF mass cytometry. Notably, cells carrying a Pro-Code/CRISPR targeting the Trp53 lost expression of the immune co-stimulatory molecule CD80. Validation confirmed that Trp53 knockout resulted in the loss of CD80 and that activation of P53, through DNA damage or stabilization, resulted in CD80 upregulation. P53 ChIP-seq identified the CD80 promoter as a direct target of P53. CD80 regulation by P53 was identified in other cells, including normal epithelial cells and macrophages. Functionally, CD80 reduction caused by P53 loss led to a reduced capacity for CRC to prime antigen-specific T cells. These studies establish CD80, a canonical co-stimulatory molecule, as a direct target of the tumor suppressor and DNA damage response gene, P53.
Splice sites obey the power-law during splicing in leukemia cells
Authors: Grinev Vasily , Siomava Natalia , Vallar Laurent , Nazarov Petr 
Published: May 2021

ABSTRACTAlternative splicing is an essential characteristic of living cells that usually infers a various exon-exon junction governed by different splice sites. The traditional classification based on the mode of use designates splice site to one of the two groups, constitutive or alternative. Here, we considered another criterion and reorganized splice sites into “unisplice” and “multisplice” groups according to the number of undertaken splicing events. This approach provided us with a new insight in the organization and functionality of leukemia cells. We determined features associated with uni- and multisplice sites and found that combinatorics of these sites follows strict rules of the power-law in the t(8;21)-positive leukemia cells. We also found that system splicing characteristics of the transcriptome of leukemia cells remained persistent after drastic changes in the transcript composition caused by knockdown of the RUNX1-RUNX1T1 oncogene. In this work, we show for the first time that leukemia cells possess a sub-set of unisplice sites with a hidden multisplice potential. These findings reveal a new side in organization and functioning of the leukemic cells and open up new perspectives in the study of the t(8;21)-positive leukemia.
Coordination of KIF3A and KIF13A regulates leading edge localization of MT1-MMP to promote cancer cell invasion
Authors: Gifford Valentina , Woskowicz Anna , Ito Noriko , Balint Stefan , Dustin Michael L. , Itoh Yoshifumi 
Published: May 2021

ABSTRACTMT1-MMP plays a crucial role in promoting the cellular invasion of cancer cells by degrading the extracellular matrix to create a path for migration. During this process, its localization at the leading edge of migrating cells is critical, and it is achieved by targeted transport of MT1-MMP-containing vesicles along microtubules by kinesin superfamily proteins (KIFs). Here we identified three KIFs involved in MT1-MMP vesicle transport: KIF3A, KIF13A, and KIF9. Knockdown of KIF3A and KIF13A effectively inhibited MT1-MMP-dependent collagen degradation and invasion, while knockdown of KIF9 increased collagen degradation and invasion. Our data suggest that KIF9 competes with KIF3A/KIF13A to bring MT1-MMP vesicles to different locations in the plasma membrane. Live-cell imaging analyses have indicated that KIF3A and KIF13A coordinate to transport the same MT1-MMP-containing vesicles. Taken together, we have identified a unique interplay between three KIFs to regulate leading edge localization of MT1-MMP and MT1-MMP-dependent cancer cell invasion.