bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Hypothesis for Migraine Disease Mechanism: The Creation of a New Attractor Responsible for Migraine Disease Symptoms
Authors: Garehdaghi Farnaz , Sarbaz Yashar , Baradari Elham 
Published: November 2022

AbstractMigraine Disease (MD) is one of the primary headaches in which the pathophysiological mechanism is yet unknown. It is still unclear how the ictal phases’ periods are determined? Why can any small trigger sometimes initiate the ictal phase, and sometimes, even bigger triggers cannot? Considering the brain as a dynamic system and proposing a complex system model for that as a migraineur or a healthy subject is a viable method. Here, the interaction between whole neurons is analyzed rather than individual neurons. This model is a complex system with a chaotic attractor. With parameter alternations, this attractor changes from one scroll to double scroll, representing a healthy or a migraineur brain. In the proposed system, the attractor’s borders are the regions where every small trigger can start the ictal phase, while the outer areas are the non-sensitive brain situations. We believe that MD and Chua’s systems have certain behavioral similarities. This study aimed to explain the function of MD and offer a theory that adequately describes its behavior. Finally, it has been tried to discuss some physiological evidences such as Migraine Generator Network (MGN), Cortical Spreading Depression (CSD), and the role of Serotonin and other substances in relation to the expressed hypotheses. This insight may propose newer methods for preventing or curing MD. Knowing the functioning of dynamic systems and finding similar behaviors with MD on the one hand, as well as linking physiological and pathophysiological evidence with a quantitative model can be very useful in better understanding, managing, and controlling the MD.
AGouTI - flexible Annotation of Genomic and Transcriptomic Intervals
Authors: Kosiński Jan G. , Żywicki Marek 
Published: November 2022

AbstractSummaryThe recent development of high-throughput workflows in genomics and transcriptomics revealed that efficient annotation is essential for effective data processing and analysis. Although a variety of tools dedicated to this purpose is available, their functionality is limited. Here, we presentAGouTI– a universal tool for flexible annotation of any genomic or transcriptomic coordinates using known genomic features deposited in different publicly available databases in the form of GTF or GFF files. In contrast to currently available tools,AGouTIis designed to provide a flexible selection of genomic features overlapping or adjacent to annotated intervals, can be used on custom column-based text files obtained from different data analysis pipelines, and supports operations on transcriptomic coordinate systems.Availability and ImplementationAGouTI was implemented using Python 3 and is freely available on GitHub (https://github.com/zywicki-lab/agouti), from the Python Package Index (https://pypi.org/project/AGouTI/) or Anaconda Cloud (https://anaconda.org/bioconda/agouti). We also provide a Galaxy wrapper available from the Galaxy Tool Shed (https://toolshed.g2.bx.psu.edu/view/janktoolshed/agouti/c204da8f836d).Supplementary informationSupplementary Data are available at Publisher site online. Files for replicating the use-case scenario described in Supplementary Data are available at Zenodo:https://doi.org/10.5281/zenodo.7317210.ContactMarek.Zywicki@amu.edu.pl
Online decoding of covert speech based on the passive perception of speech
Authors: Moon Jae , Chau Tom 
Published: November 2022

AbstractBackgroundBrain-computer interfaces (BCIs) can offer solutions to communicative impairments induced by conditions such as locked-in syndrome. While covert speech-based BCIs have garnered interest, a major issue facing their clinical translation is the collection of sufficient volumes of high signal-to-noise ratio (SNR) examples of covert speech signals which can typically induce fatigue in users. Fortuitously, investigations into the linkage between covert speech and speech perception have revealed spatiotemporal similarities suggestive of shared encoding mechanisms. Here, we sought to demonstrate that an electroencephalographic cross-condition machine learning model of speech perception and covert speech can successfully decode neural speech patterns during online BCI scenarios.MethodsIn the current study, ten participants underwent a dyadic protocol whereby participants perceived the audio of a randomly chosen word and then subsequently mentally rehearsed it. Eight words were used during the offline sessions and subsequently narrowed down to three classes for the online session (two words, rest). The modelling was achieved by estimating a functional mapping derived from speech perception and covert speech signals of the same speech token (features were extracted via a Riemannian approach).ResultsWhile most covert speech BCIs deal with binary and offline classifications, we report an average ternary and online BCI accuracy of 75.3% (60% chance-level), reaching up to 93% in select participants. Moreover, we found that perception-covert modelling effectively enhanced the SNR of covert speech signals correlatively to their high-frequency correspondences.ConclusionsThese findings may pave the way to efficient and more user-friendly data collection for passively training such BCIs. Future iterations of this BCI can lead to a combination of audiobooks and unsupervised learning to train a non-trivial vocabulary that can support proto-naturalistic communication.Significance StatementCovert speech brain-computer interfaces (BCIs) provide new communication channels. However, these BCIs face practical challenges in collecting large volumes of high-quality covert speech data which can both induce fatigue and degrade BCI performance. This study leverages the reported spatiotemporal correspondences between covert speech and speech perception by deriving a functional mapping between them. While multiclass and online covert speech classification has previously been challenging, this study reports an average ternary and online classification accuracy of 75.3%, reaching up to 93% for select participants. Moreover, the current modelling approach augmented the signal-to-noise ratio of covert speech signals correlatively to their gamma-band correspondences. The proposed approach may pave the way toward a more efficient and user-friendly method of training covert speech BCIs.
Cultivation and Fluorescent in situ hybridization suggest that some shipworm species acquire endosymbiotic bacteria through indirect horizontal transmission
Authors: Speare Lauren , Distel Daniel L 
Published: November 2022

ABSTRACTBeneficial microbial symbionts provide essential functions for their host from nutrients to defense against disease. Whether hosts acquire their symbionts directly from parents (vertical transmission) or by sampling from the environment (horizontal transmission) can have dramatic impacts on host adaptability and, in the case of ecosystem engineers, ecosystem health. Wood-boring bivalve mollusks (Teredinidae shipworms) act as ecosystem engineers in marine environments, creating habitat out of submerged wood for fish and invertebrates. Essential to shipworm success is their community of endosymbiotic gill bacteria that produce the enzymes necessary for wood digestion. How shipworms acquire their symbionts, however, remains largely unexplored. Using culturing, fluorescencein-situhybridization, confocal microscopy, and tank experiments, we provide evidence suggesting the mode of symbiont transmission the shipworms for either the shipworm,Lyrodus pedicellatusorTeredo bartschior both. Symbiotic bacteria were not detected by cultivation or microscopy in brooding larvae within gravid adults or as veliger larvae collected from the water column, but were observed in adult specimens and juveniles that had begun burrowing into wood. These data suggest that the specimens examined have both aposymbiotic and symbiotic life phases and acquire their symbionts through indirect horizontal transmission. Our findings reveal how the long-term broodersL. pedicellatusand/orT. bartschiacquire their gill endosymbionts.IMPORTANCEHow eukaryotic hosts acquire their microbial symbionts can have significant consequences for their ability to adapt to varied environments. Although wood-boring bivalve shipworms have diverse reproductive strategies and are found in unique environments across the globe, little is known about how they transmit their essential gill endosymbionts. We used the closely related shipworms,Lyrodus pedicellatusand/orTeredo bartschito study how these long-term brooding shipworms acquire their gill endosymbionts. Our work, unlike previous claims for the broadcast spawning speciesBankia setacaewhich reportedly transmits its symbionts directly from parent to offspring, suggests that juvenileL. pedicellatusand/orT. bartschiacquire their symbionts through horizontal transmission rather than directly from their parents. This work reveals the mechanism by which some brooding shipworm species acquire their symbionts, adding to our limited understanding of intracellular symbiont transmission of Teredinidae.
The ground offers acoustic efficiency gains for crickets and other calling animals
Authors: Brandt Erin E. , Duke Sarah , Wang Honglin , Mhatre Natasha 
Published: November 2022

AbstractMale crickets attract females by producing calls with their forewings. Louder calls travel further and are more effective at attracting mates. However, crickets are much smaller than the wavelength of their call, and this limits their power output. A small group called tree crickets make acoustic tools called baffles which reduce acoustic short-circuiting, a source of dipole inefficiency. Here, we ask why baffling is uncommon among crickets. We hypothesize that baffling may be rare, because like other tools they offer insufficient advantage for most species. To test this, we modelled the calling efficiencies of crickets within the full space of possible natural wing sizes and call frequencies, in multiple acoustic environments. We then generated efficiency landscapes, within which we plotted 112 cricket species across 7 phylogenetic clades. We found that all sampled crickets, in all conditions, could gain efficiency from tool use. Surprisingly, we also found that calling from the ground significantly increased efficiency, with or without a baffle, by as much as an order of magnitude. We found that the ground provides some reduction of acoustic short-circuiting but also halves the air volume within which sound is radiated. It simultaneously reflects sound upwards, allowing recapture of a significant amount of acoustic energy through constructive interference. Thus, using the ground as a reflective baffle is an effective strategy for increasing calling efficiency. Indeed, theory suggests that this increase in efficiency is accessible not just to crickets, but to all acoustically communicating animals whether they are dipole or monopole sound sources.Significance StatementLoudness is a crucial feature in acoustic communication. Animals attracting mates or warding off predators are expected to make themselves as loud as possible. Two long-standing, seemingly unrelated unsolved problems regarding loudness in the field of animal communication are: the rarity of acoustic tool use, and animals that call from reflective ground-like surfaces, known to be an impediment to sound propagation. These two ideas are related; by refocusing analysis from sound propagation to sound radiation, we show that the ground is not an impediment, but rather an acoustic aid that can boost loudness more than tool use. We also show that calling from a reflective surface is an alternative strategy to maximize call loudness that is available to all animals.
A universal differential expression prediction tool for single-cell and spatial genomics data
Authors: Vandenbon Alexis , Diez Diego 
Published: November 2022

ABSTRACTWith the growing complexity of single-cell and spatial genomics data, there is an increasing importance of unbiased and efficient exploratory data analysis tools. One common exploratory data analysis step is the prediction of genes with different levels of activity in a subset of cells or locations inside a tissue. We previously developed singleCellHaystack, a method for predicting differentially expressed genes from single-cell transcriptome data, without relying on clustering of cells. Here we present an update to singleCellHaystack, which is now a universally applicable method for predicting differentially active features: 1) singleCellHaystack now accepts continuous features that can be RNA or protein expression, chromatin accessibility or module scores from single-cell, spatial and even bulk genomics data, and 2) it can handle 1D trajectories, 2-3D spatial coordinates, as well as higher-dimensional latent spaces as input coordinates. Performance has been drastically improved, with up to ten times reduction in computational time and scalability to millions of cells, making singleCellHaystack a suitable tool for exploratory analysis of atlas level datasets. singleCellHaystack is available as an R package and Python module
Risk factors for extended-spectrum beta-lactamase (ESBL) producingE. colicarriage among children in a food animal producing region of Quito, Ecuador
Authors: Amato Heather K. , Loayza Fernanda , Salinas Liseth , Paredes Diana , Garcia Daniela , Sarzosa Soledad , Saraiva-Garcia Carlos , Johnson Timothy J. , Pickering Amy J. , Riley Lee W. , Trueba Gabriel , Graham Jay P. 
Published: November 2022

AbstractBackgroundThe spread of antibiotic-resistant bacteria may be driven by human-animal-environment interactions, especially in regions with limited restrictions on antibiotic use, widespread food animal production, and free-roaming domestic animals. In this study, we aimed to identify risk factors related to domestic animals, backyard food animals, and commercial food animal production in Ecuadorian communities.Methods & FindingsWe conducted a repeated-measures study from 2018-2021 in 7 semi-rural parishes of Quito, Ecuador to identify determinants of third-generation cephalosporin-resistantE. coli(3GCR-EC) and extended-spectrum beta-lactamaseE. coli(ESBL-EC) in children and domestic animals. We used multivariable log-binomial regression models to estimate relative risks (RR) of 3GCR-EC and ESBL-EC carriage. We collected 1,699 child fecal samples from 600 households and 1,871 animal fecal samples from 376 of the same households. Risk factors for 3GCR-EC included living within 5 km of more than 5 commercial food animal operations (RR: 1.36; 95% Confidence Interval: 1.16, 1.59), household pig ownership (1.23; 1.02, 1.48), child pet contact (1.23; 1.09, 1.39), and rarely/never washing hands after contact with animals (1.15; 0.98, 1.34). Risk factors for ESBL-EC were dog ownership (1.43; 1.00, 2.04), child pet contact (1.54; 1.10, 2.16), placing animal feces on household land/crops (1.63; 1.09, 2.46), and combined exposures to both household food animals and commercial food animal operation drainage paths (1.80; 0.94, 3.45).ConclusionsPolicies and interventions that improve the safety of animal waste management in communities and in commercial food animal production operations may be necessary to curb the spread of resistant bacteria.
Risk factors and symptom clusters for Long Covid: analysis of United Kingdom symptom tracker app data
Authors: Ford Elizabeth , Parfitt Harley , McCheyne Ian , Kiss István Z. , Sellers Ruth 
Published: November 2022

AbstractBackgroundLong Covid, characterised by symptoms after Covid-19 infection which persist for longer than 12 weeks, is becoming an important societal and economic problem. As Long Covid was novel in 2020, there has been debate regarding its aetiology and whether it is one, or multiple, syndromes. This study assessed risk factors associated with Long Covid and examined symptom clusters that might indicate sub-types.Methods4,040 participants reporting for >4 months in the Covid Symptom Study App were included. Multivariate logistic regression was undertaken to identify risk factors associated with Long Covid. Cluster analysis (K-modes and hierarchical agglomerative clustering) and factor analysis were undertaken to investigate symptom clusters.ResultsLong Covid affected 13.6% of participants. Significant risk factors included being female (P< 0.01), pre-existing poor health (P< 0.01), and worse symptoms in the initial illness. A model incorporating sociodemographics, comorbidities, and health status predicted Long Covid with an accuracy (AUROC) of 76%. The three clustering approaches gave rise to different sets of clusters with no consistent pattern across methods.ConclusionsOur model of risk factors may help clinicians predict patients at higher risk of Long Covid, so these patients can rest more, receive treatments, or enter clinical trials; reducing the burden of this long-term and debilitating condition. No consistent subtypes were identified.
The GxcM-Fbp17/RacC-WASP signaling cascade regulates polarized cortex assembly in migrating cells
Authors: Li Dong , Yang Yihong , Wang Yingjie , Chao Xiaoting , Huang Jiafeng , Singh Shashi P. , Zhang Chengyu , Lou Jizhong , Gao Pu , Huang Shanjin , Cai Huaqing 
Published: November 2022

AbstractThe actin-rich cortex plays a fundamental role in many cellular processes. Its architecture and molecular composition vary across cell types and physiological states. The full complement of actin assembly factors driving cortex formation and how their activities are spatiotemporally regulated remain to be fully elucidated. UsingDictyosteliumas a model for polarized and rapidly migrating cells, we show that GxcM, a RhoGEF localized specifically in the rear of migrating cells, functions together with F-BAR protein Fbp17, a small GTPase RacC, and the actin nucleation-promoting factor WASP to coordinately promote Arp2/3 complex-mediated cortical actin assembly. Over-activation of this signaling cascade leads to excessive actin polymerization in the rear cortex, whereas its disruption causes defects in cortical integrity and function. Therefore, different from its well-defined role in the formation of the front protrusions, the Arp2/3 complex-based actin carries out a previously unappreciated function in building the rear cortical subcompartment in rapidly migrating cells.
Single-cell sequencing of Entorhinal Cortex Reveals Wide-Spread Disruption of Neuropeptide Networks in Alzheimer’s Disease
Authors: Li Manci , Larsen Peter A. 
Published: November 2022

AbstractAlzheimer’s disease (AD) is a fatal neurodegenerative disease that involves early and significant neuropathological changes within the entorhinal cortex (EC). Many have reported on neuronal loss and synaptic dysfunction in the brains of AD patients and AD models. In parallel, abnormalities of neuropeptides (NPs) that play important roles in modulating neuronal activities are commonly observed in AD and other neurodegenerative diseases. However, the involvement of NPs has mostly been studied in the context of neurons; a cell type-specific examination of NP expression in AD brains is needed. Here, we aim to examine the NP networks in the EC of AD brains using single-nuclei and bulk transcriptomic data from other regions in the temporal cortex, focusing on the gene expression of NP and their cognate G-protein coupled receptors. We find that NP genes were expressed by all major cell types in the brain and there was a significant decrease in the quantity and the proportion of cells that express NPs in AD EC cells. On the contrary, the overall expression of GPCR genes showed an increase in AD cells, likely reflecting ongoing compensatory mechanisms in AD brains. In addition, we report that there was a disproportionate absence of cells expressing higher levels and greater diversity of NPs in AD brains. Finally, we established a negative correlation between age and the abundance of AD-associated NPs in the hippocampus, supporting that the disruption of the NP signaling network in the EC may contribute to the early pathogenesis of AD. In short, we report widespread disruption of the NP networks in AD brains at the single-cell level. In light of our results, we hypothesize that brain cells, especially neurons, that express high levels of NPs may exhibit selective vulnerability to AD. Moreover, it is likely AD brains undergo specific adaptive changes to fluctuating NP signaling, a process that can likely be targeted with therapeutic approaches aimed at stabilizing NP expression landscapes. Given that GPCRs are one of the most druggable targets for neurological diseases and disorders, we believe NP signaling pathways can be harnessed for future biomarkers and treatment strategies for AD.
Structural Reorganization Following a Brain Tumor: A Machine Learning Study Considering Desynchronized Functional Oscillations
Authors: Falcó-Roget Joan , Sambataro Fabio , Cacciola Alberto , Crimi Alessandro 
Published: November 2022

AbstractNeuroimaging studies have allowed for non-invasive mapping of brain networks in brain tumors. Although tumor core and oedema are easily identifiable using standard MRI acquisitions, imaging studies often neglect signals, structures and functions within their presence. Therefore, both functional and diffusion signals, as well as their relationship with global patterns of connectivity reorganization, are poorly understood. Here, we explore functional activity and the structure of white matter fibers considering the contribution of the whole tumor in a surgical context. First, we find that intra-tumor signals do exist and are correlated with alterations present both in healthy tissue and resting-state networks. Second, we propose a fiber tracking pipeline capable of using anatomical information while still reconstructing bundles in tumoral and peritumoral tissue. Finally, using machine learning and healthy anatomical information, we predict structural rearrangement after surgery given the preoperative brain network. The generative model also disentangles complex patterns of connectivity reorganization for different types of tumors. Overall, we show the importance of carefully designing studies including MR signals within damaged brain tissues, as they exhibit and relate to non-trivial patterns of both structural and functional (dis-)connections or activity.