bluuebunny/crossref_metadata_2025_split huggingface dataset:
Snapper: a high-sensitive algorithm to detect methylation motifs based on Oxford Nanopore reads
Authors: Konanov Dmitry N. , Babenko Vladislav V. , Belova Aleksandra M. , Madan Arina G. , Boldyreva Daria I. , Glushchenko Oksana E. , Butenko Ivan O. , Fedorov Dmitry E. , Manolov Aleksandr I. , Lazarev Vassili N. , Govorun Vadim M. , Ilina Elena N. 
Published: November 2022

AbstractThe Oxford Nanopore technology has a great potential for the analysis of genome methylation, including full-genome methylome profiling. However, there are certain issues while identifying methylation motif sequences caused by low sensitivity of the currently available motif enrichment algorithms. Here, we present Snapper, a new highly-sensitive approach to extract methylation motif sequences based on a greedy motif selection algorithm. Snapper has shown higher enrichment sensitivity compared with the MEME tool coupled with Tombo or Nanodisco instruments, which was demonstrated onH. pyloristrain J99 studied earlier using the PacBio technology. In addition, we used Snapper to characterize the total methylome of a newH.pyloristrain A45. The analysis revealed the presence of at least 4 methylation sites that have not been described forH. pyloriearlier. We experimentally confirmed a new CCAG-specific methyltransferase and indirectly inferred a new CCAAK-specific methyltransferase.
Characterizing the landscape of gene expression variance in humans
Authors: Wolf Scott , Melo Diogo , Garske Kristina M. , Pallares Luisa F. , Lea Amanda J. , Ayroles Julien F. 
Published: November 2022

AbstractGene expression variance has been linked to organismal function and fitness but remains a commonly ne-glected aspect of molecular research. As a result, we lack a comprehensive understanding of the patterns of transcriptional variance across genes, and how this variance is linked to context-specific gene regulation and gene function. Here, we use 57 large publicly available RNA-seq data sets to investigate the landscape of gene expression variance. These studies cover a wide range of tissues and allowed us to assess if there are consistently more or less variable genes across tissues and data sets and what mechanisms drive these patterns. We show that gene expression variance is broadly similar across tissues and studies, indicating that the pattern of transcriptional variance is consistent. We use this similarity to create both global and within-tissue rankings of variation, which we use to show that function, sequence variation, and gene regulatory signatures contribute to gene expression variance. Low-variance genes are associated with fundamental cell processes and have lower levels of genetic polymorphisms, have higher gene-gene connectivity, and tend to be associated with chromatin states associated with transcription. In contrast, high-variance genes are enriched for genes involved in immune response, environmentally responsive genes, immediate early genes, and are associated with higher levels of polymorphisms. These results show that the pattern of transcriptional variance is not noise. Instead, it is a consistent gene trait that seems to be functionally constrained in human populations. Furthermore, this commonly neglected aspect of molecular phenotypic variation harbors important information to understand complex traits and disease.Author SummaryGene expression variance, or the variation in the level of gene expression within a population, can have significant impacts on physiology, disease, and evolutionary adaptations. While the average level of gene expression is typically the focus of research, the variation around this average level (i.e., gene expression variance) can also be important for understanding complex traits and disease. Here, we investigate the landscape of transcriptional variance across tissues, populations, and studies. Using large publicly available RNA-seq data sets, we were able to identify the general properties associated with high- and low-variance genes, as well as factors driving variation in variance across genes. Specifically, we uncovered gene expression variance was significantly associated with gene length, nucleotide diversity, the degree of connectivity and the presence of non-coding RNA. Our results suggest that the mechanisms responsible for maintaining optimal levels of variation in high-versus low-variance differ, and that this variability is the result of different patterns of selection.
Bidirectional epigenetic editing reveals hierarchies in gene regulation
Authors: Pacalin Naomi M. , Shi Quanming , Parker Kevin R. , Chang Howard Y. 
Published: November 2022

ABSTRACTCRISPR perturbations are valuable tools for studying the functional effects of the genome. However, existing methods are limited in their utility for studying noncoding elements and genetic interactions. Here, we develop a system for bidirectional epigenetic editing (CRISPRai), in which orthogonal activating (CRISPRa) and repressive (CRISPRi) perturbations are applied simultaneously to multiple loci the same cell. We developed dual-gRNA-capture single-cell Perturb-seq to study the established interaction between SPI1 and GATA1, two hemopoietic lineage transcription factors, and discovered novel context-specific regulation modes for co-regulated genes. Extending CRISPRai to noncoding elements, we addressed how multiple enhancers interact to modulate expression of a shared target gene, Interleukin-2, in T cells. We found that enhancer function was primarily additive and enabled fine-tuning of gene expression, yet a clear hierarchy existed among enhancers in strength of gene expression control. The promoter was dominant over most enhancers in controlling gene expression; however, a small subset of enhancers exhibited strong functional effects, or gatekeeper function, and could turn off the gene despite promoter activation. Integration of these functional data with histone ChIP-seq and TF motif enrichment suggests the existence of multiple modes of enhancer-mediated gene regulation. Our method, CRISPRai for bidirectional epigenetic editing, provides an approach for identifying novel genetic interactions that may be overlooked when studied without bidirectional perturbations and can be applied to both genes and noncoding elements.
Defining the Parameters to Improve Plant Regeneration with Developmental Regulators
Authors: Nasti Ryan , Cody Jon P. , Zinselmeier Matt H. , Badey Nikil B. , Sridhar Adhvaith , Sharma Ambika , Maher Michael F. , Blackman Benjamin K. , Voytas Daniel F. 
Published: November 2022

AbstractTissue culture methods which serve as the standard to regenerate modified plants are challenging and have limited the capacity to engineer new accessions. To improve upon these techniques, genome modifying reagents have been combined with developmental regulators to create gene edited plant tissues in both monocot and eudicot species. Co-culturing seedlings with Agrobacterium strains encoding developmental regulatory genes has proved to be effective at producingde novomeristems in multiple eudicot species. In order to see that this technology scales well beyond proof of concept experiments, various parameters were tested for refinement. Improvements have been observed at the key stages of growth induction and progression to shooting by manipulating the vector design, developmental regulator choice, Agrobacterium strain selection, and regulatory gene removal systems. Having defined these parameters as viable optimization points, the avenues to apply developmental regulators for plant regeneration in more diverse species have become more feasible.
A Framework for Better Sensor-Based Beehive Health Monitoring
Authors: Zaman Asaduz , Dorin Alan 
Published: November 2022

AbstractHive bees provide essential pollination services to human agriculture. Managed honey bees in particular pollinate many crops, but also create honey and other bee products that are now of global economic importance. Key aspects of honey bee behaviour can be understood by observing hives. Hence, the limitations of manual observation are increasingly being addressed by new technologies that automate and extend the reach of hive monitoring.Here we propose a framework to classify and clarify the potential for sensor-assisted hive monitoring to inform apiculture and, ultimately, improve hive bee management. This framework considers hive monitoring approaches across three newly proposed categories: Operational monitoring, Investigative monitoring, and Predictive monitoring. These categories constitute a new “OIP Framework” of hive monitoring. Each category has its own requirements for underlying technology that includes sensors and ICT resources we outline. Each category is associated with particular outcomes and benefits for apiculture and hive health monitoring detailed here. Application of these three classes of sensor-assisted hive monitoring can simplify understanding and improve best-practice management of hive bees.Our survey and classification of hive monitoring to date show that it is seldom practiced beyond honey bees, despite the need to understand bumble bees and stingless bees also. Perhaps unsurprisingly, sensor-based hive monitoring is shown to remain primarily a practice of developed nations. Yet we show how all countries, especially developing nations, stand to gain substantially from the benefits improved sensor-based hive monitoring offers. These include a better understanding of environmental change, an increased ability to manage pollination, an ability to respond rapidly to hive health issues such as pests and pathogens, and even an ability to react quickly to the danger posed to insects and humans alike by extreme events such as floods and fires. Finally, we anticipate that the future of hive monitoring lies in the application of Predictive monitoring, such that a hive’s anticipated future state can be preemptively managed by beekeepers working iteratively with novel hive monitoring technologies.
The neuropeptide FLP-17 regulates an oviposition behavior in the nematodeCaenorhabditis elegansthat increases maternal reproductive fitness in low oxygen environments
Authors: Lee Tong Young , Chang Eunha , Yoon Kyoung-hye , Lee Jin I. 
Published: November 2022

SUMMARYThe ability for animals to adapt their behaviors to specific environments is imperative to increase their evolutionary success. This is particularly true for behaviors such as parental behaviors that directly affect reproductive fitness. Here, we identified an oviposition behavior in the nematodeC. elegansthat increases the survival of the young. In standard laboratory culture, the bacterivorous hermaphrodite mothers lay eggs across a 2DE. colilawn with no discernable pattern. However, in 3D culture they display a stereotypical behavior in which they temporarily leave the bacteria to lay eggs far away from theE. colicolony, resulting in a scattered ring of eggs located outside the bacteria. This oviposition behavior requires low oxygen levels and is regulated by the neuropeptide FLP-17 and its cognate receptor EGL-6. We confirm that a circuitry involving the oxygen-sensing BAG neurons and the vulva muscle-controlling HSN motor neurons regulates oviposition behavior. We show that loss of proper oviposition behavior results in lower reproductive fitness for the mothers and embryonic lethality for the eggs laid in bacteria under hypoxic conditions. Finally, we show that the degree of oviposition behavior varies among wild strains ofC. elegansfound in nature. The ability forC. elegansmothers to sense their environments and adjust their behaviors in adverse conditions is likely an adaptation that has allowed the worm to thrive in diverse and often hazardous habitats.
Endothelial Caveolin-1 and CXCL10 promote transcellular migration of autoreactive T cells across the blood-brain barrier
Authors: Trevino Troy N. , Almousawi Ali A. , Ochoa-Raya Andrea , Zemanski Kait , Oliveira Suellen DS , Marottoli Felecia M. , Tai Leon M. , Minshall Richard D. , Lutz Sarah E. 
Published: November 2022

AbstractCXCL10 is an interferon-inducible chemokine that can recruit CXCR3+leukocytes to the central nervous system, leading to neuroinflammation, demyelination, and neuronal losses. How CXCL10 promotes leukocyte extravasation and diapedesis across the blood-brain barrier – formed by brain endothelial cells – is poorly understood. Here, we report that CXCL10 mediates CD4+ T cell migration through the brain endothelial cell cytoplasm (transcellular), but not cell-cell junctions (paracellular), via the vesicular trafficking protein Caveolin-1. Caveolin-1 promotes CXCL10 aggregation into cytoplasmic stores in brain endothelial cellsin vitroto provide the local, high concentration necessary for recruitment of CXCR3+ leukocytes. This process also requires LFA-1 activity. In the absence of Caveolin-1, endothelial CXCL10 is secreted, and the local signaling cues are lost. Consistent with ourin vitrodata, genetic ablation of Caveolin-1 in endothelial cells reduces the severity of active experimental autoimmune encephalomyelitis (EAE), a murine model for multiple sclerosis, by decreasing the infiltration of CXCR3+ T cells into the CNS. Moreover, loss of Caveolin-1 protects against the adoptive transfer of autoreactive T cells. Our findings establish a novel mechanism by which brain endothelial cells utilize Caveolin-1 dependent CXCL10 intracellular stores to license T cells for transcellular migration across the blood-brain barrier.
Flow-induced mechanical coupling between perinuclear actin cap and nucleus governs spatiotemporal regulation of YAP transport
Authors: Ma Tianxiang , Liu Xiao , Su Haoran , He Yuan , Wu Fan , Gao Chenxing , Li Kexin , Liang Zhuqing , Zhang Dongrui , Zhang Xing , Hu Ke , Li Shangyu , Wang Li , Wang Min , Yue Shuhua , Hong Weili , Chen Xun , Zhang Jing , Deng Xiaoyan , Wang Pu , Fan Yubo 
Published: November 2022

AbstractMechanical forces, including flow shear stress, regulate fundamental cellular process by modulating the nucleocytoplasmic transport of transcription factors, such as Yes-associated Protein (YAP). However, the mechanical mechanism how flow induces the nucleocytoplasmic transport remains largely unclear. Here we found that unidirectional flow applied to endothelial cells induces biphasic YAP nucleocytoplasmic transport with initial nuclear import, followed by nuclear export as perinuclear actin cap forms and nuclear stiffening in a dose and timing-dependent manner. In contrast, pathological oscillatory flow induces slight actin cap formation and nuclear softening, sustaining YAP nuclear localization. To explain the disparately spatiotemporal distribution of YAP, we developed a three-dimensional mechanochemical model considering coupling processes of flow sensing, cytoskeleton organization, nucleus mechanotransduction, and YAP spatiotemporal transport. We discovered that actin cap formation and nuclear stiffness alteration under flow synergically regulate nuclear deformation, hence governing YAP transport. Furthermore, we expanded our single cell model to a collective vertex framework and found that actin cap irregularities in individual cells under flow shear stress potentially induce topological defects and spatially heterogeneous YAP distribution in cellular monolayers. Our work unveils the unified mechanism of flow-induced nucleocytoplasmic transport, offering a universal linkage between transcriptional regulation and mechanical stimulation.
Molecular epidemiology of Infectious Spleen and Kidney Necrosis Virus (ISKNV) in Ghanaian cultured tilapia
Authors: Ayiku Angela Naa Amerley , Adelani Abigail Akosua , Appenteng Patrick , Nkansah Mary , Ngoi Joyce M. , Morang’a Collins Misita , Paley Richard , Cudjoe Kofitsyo S. , Verner-Jeffreys David , Quashie Peter Kojo , Duodu Samuel 
Published: November 2022

1ABSTRACTInfectious Spleen and Kidney Necrosis Virus (ISKNV) is increasingly gaining more attention globally, due to its highly significant economic impact on the aquaculture industry. In late 2018, unusually high levels of mortality (60-90%) was reported in some intensive tilapia cage culture systems in Ghana. Preliminary investigations confirmed the involvement of ISKNV, a viral pathogen noted for fatal systemic infections in many fish species. As a follow-up on the outbreak situation, and post-mass vaccination of affected fish farms, the need to investigate further the molecular epidemiology and phylogeography of the virus across Lake Volta became paramount. In this study, a multiplexed PCR assay and MinION™ nanopore sequencing of the Major Capsid Protein (MCP) were performed to investigate the presence and genotype of ISKNV in tilapia collected from 30 randomly selected farms spread across Lake Volta. Fish with and without clinical signs were included in the molecular detection of the virus from brain, kidney and spleen tissues. ISKNV was detected at 80% prevalence with fry and juvenile fish being most affected. Phylogenetic analysis of the MCP revealed that all 35 isolates from 14 different farms were ISKNV genotype I with near- 100% homology to the 2018 outbreak strain. Vaccination and heat shock treatment; the main specific interventions currently employed to control the viral pathogen have not achieved much success and ISKNV remains a threat to the growth of the aquaculture industry in Ghana. The outcome of this study can be useful in improving fish health management and biosecurity policies in the aquaculture industry.
gGN: learning to represent graph nodes as low-rank Gaussian distributions
Authors: Edera Alejandro A. , Stegmayer Georgina , Milone Diego H. 
Published: November 2022

AbstractUnsupervised learning of node representations from knowledge graphs is critical for numerous downstream tasks, ranging from large-scale graph analysis to measuring semantic similarity between nodes. This study presents gGN as a novel representation that defines graph nodes as Gaussian distributions. Unlike existing representations that approximate such distributions using diagonal covariance matrices, our proposal approximates them using low-rank perturbations. We demonstrate that this low-rank approximation is more expressive and better suited to represent complex asymmetric relations between nodes. In addition, we provide a computationally affordable algorithm for learning the low-rank representations in an unsupervised fashion. This learning algorithm uses a novel loss function based on the reverse Kullback-Leibler divergence and two ranking metrics whose joint minimization results in node representations that preserve not only node depths but also local and global asymmetric relationships between nodes. We assessed the representation power of the low-rank approximation with an in-depth systematic empirical study. The results show that our proposal was significantly better than the diagonal approximation for preserving graph structures. Moreover, gGN also outperformed 17 methods on the downstream task of measuring semantic similarity between graph nodes.
Particulate matter air pollution and COVID-19 infection, severity, and mortality: A systematic review
Authors: Sheppard Nicola , Carroll Matthew , Gao Caroline , Lane Tyler 
Published: November 2022

AbstractBackground and objectiveEcological studies indicate ambient particulate matter ≤2.5mm (PM2.5) air pollution is associated with poorer COVID-19 outcomes. However, these studies cannot account for individual heterogeneity and often have imprecise estimates of PM2.5exposure. We review evidence from studies using individual-level data to determine whether PM2.5increases risk of COVID-19 infection, severe disease, and death.MethodsSystematic review of case-control and cohort studies, searching Medline, Embase, and WHO COVID-19 up to 30 June 2022. Study quality was evaluated using the Newcastle-Ottawa Scale. Results were pooled with a random effects meta-analysis, with Egger’s regression, funnel plots, and leave-one-out and trim-and-fill analyses to adjust for publication bias.ResultsN=18 studies met inclusion criteria. A 10μg/m3 increase in PM2.5exposure was associated with 66% (95% CI: 1.31-2.11) greater odds of COVID-19 infection (N=7) and 127% (95% CI: 1.41-3.66) increase in severe illness (hospitalisation or worse) (N=6). Pooled mortality results (N=5) were positive but non-significant (OR 1.40; 0.94 to 2.10). Most studies were rated “good” quality (14/18 studies), though there were numerous methodological issues; few used individual-level data to adjust for confounders like socioeconomic status (4/18 studies), instead using area-based indicators (12/18 studies) or not adjusting for it (3/18 studies). Most severity (9/10 studies) and mortality studies (5/6 studies) were based on people already diagnosed COVID-19, potentially introducing collider bias.ConclusionThere is strong evidence that ambient PM2.5increases the risk of COVID-19 infection, and weaker evidence of increases in severe disease and mortality.FundingThis review was completed as a Scholarly Intensive Placement project by NS, which received no funding.Competing interestsThe authors declare no competing interests.RegistrationThis study was registered on PROSPERO on 8 July 2022 (CRD42022345129):https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022345129
The perceptual nature of illusory object recognition
Authors: Alilović Josipa , Lampers Eline , Slagter Heleen A. , van Gaal Simon 
Published: November 2022

AbstractWe occasionally misinterpret ambiguous sensory input or report a stimulus when none is presented. It is unknown whether such errors have a sensory origin and reflect true perceptual illusions, or whether they have a more cognitive origin (e.g., are due to guessing), or both. When participants performed an error-prone and challenging face/house discrimination task, multivariate EEG analyses revealed that during decision errors (mistaking a face for a house), sensory stages of visual information processing initially represent the presented stimulus category. Crucially however, when participants were confident in their erroneous decision, so when the illusion was strongest, this neural representation flipped later in time and reflected the incorrectly reported percept. This flip in neural pattern was absent for decisions that were made with low confidence. This work demonstrates that decision confidence arbitrates between perceptual decision errors, which reflect true illusions of perception, and cognitive decision errors, which do not.