bluuebunny/crossref_metadata_2025_split huggingface dataset:
The unexpected dynamics of COVID-19 in Manaus, Brazil: Was herd immunity achieved?
Authors: He Daihai , Artzy-Randrup Yael , Musa Salihu S. , Gräf Tiago , Naveca Felipe , Stone Lewi 
Published: February 2021

AbstractIn late March 2020, SARS-CoV-2 arrived in Manaus, Brazil, and rapidly developed into a large-scale epidemic that collapsed the local health system, and resulted in extreme death rates. Several key studies reported that ∼76% of residents of Manaus were infected (attack rate AR≃76%) by October 2020, suggesting protective herd immunity had been reached. Despite this, in November an unexpected second wave of COVID-19 struck again, and proved to be larger than the first creating a catastrophe for the unprepared population. It has been suggested that this could only be possible if the second wave was driven by reinfections. Here we use novel methods to model the epidemic from mortality data, evaluate the impact of interventions, in order to provide an alternative explanation as to why the second wave appeared. The method fits a “flexible” reproductive number R0(t) that changes over the epidemic, and found AR≃30-34% by October 2020, for the first wave, which is far less than required for herd immunity, yet in-line with recent seroprevalence estimates. The two-strain model provides an accurate fit to observed epidemic datasets, and finds AR≃70% by March 2021. Using genomic data, the model estimates transmissibility of the new P.1 virus lineage, as 1.9 times as transmissible as the non-P1. The model thus provides a reasonable explanation for the two-wave dynamics in Manaus, without the need to rely on reinfections which until now have only been found in small numbers in recent surveillance efforts.SignificanceThis paper explores the concept of herd immunity and approaches for assessing attack rate during the explosive outbreak of COVID-19 in the city of Manaus, Brazil. The event has been repeatedly used to exemplify the epidemiological dynamics of the disease and the phenomenon of herd immunity, as claimed to be achieved by the end of the first wave in October 2020. A novel modelling approach reconstructs these events, specifically in the presence of interventions. The analysis finds herd immunity was far from being attained, and thus a second wave was readily possible, as tragically occurred in reality. Based on genomic data, the multi-strain model gives insights on the new highly transmissible variant of concern P.1 and role of reinfection.
Roadkill islands: carnivore extinction shifts seasonal use of roadside carrion by generalist avian scavenger
Authors: Fielding Matthew W. , Buettel Jessie C. , Brook Barry W. , Stojanovic Dejan , Yates Luke A. 
Published: February 2021

AbstractGlobal road networks facilitate habitat modification and are integral to human expansion. Many animals, particularly scavengers, use roads as they provide a reliable source of food, such as carrion left after vehicle collisions. Tasmania is often cited as the ‘roadkill capital of Australia’, with the isolated offshore islands in the Bass Strait experiencing similar, if not higher, levels of roadkill. However, native mammalian predators on the islands are extirpated, meaning the remaining scavengers are likely to experience lower interference competition.In this study, we use a naturally occurring experiment to examine how the loss of mammalian carnivores within a community impacts roadside foraging behaviour by avian scavengers.We monitored the locations of roadkill and forest ravens (Corvus tasmanicus), an abundant scavenger species, on eight road transects across the Tasmanian mainland (high scavenging competition) and the Bass Strait islands (low scavenging competition). We represented raven observations as one-dimensional point patterns, using hierarchical Bayesian models to investigate the dependence of raven spatial intensity on habitat, season, distance to roadkill and route location.We found that roadkill carcasses were a strong predictor of raven presence along road networks. The effect of roadkill was amplified on roads on the Bass Strait islands, where roadside carrion was a predictor of raven presence across the entire year. In contrast, ravens were more often associated with roadkill on Tasmanian mainland roads in the autumn, when other resources were low. This suggests that in the absence of competing mammalian scavengers, ravens choose to feed on roadside carrion throughout the year, even in seasons when other resources are available. This low interference competition could be disproportionately benefiting forest ravens, leading to augmented raven populations and changes to the vertebrate community structure.Our study provides evidence that scavengers modify their behaviour in response to reduced scavenger species diversity, potentially triggering trophic shifts and highlighting the importance of conserving or reintroducing carnivores within ecosystems.
ClusterMap: multi-scale clustering analysis of spatial gene expression
Authors: He Yichun , Tang Xin , Huang Jiahao , Zhou Haowen , Chen Kevin , Liu Albert , Ren Jingyi , Shi Hailing , Lin Zuwan , Li Qiang , Aditham Abhishek , Shu Jian , Liu Jia , Wang Xiao 
Published: February 2021

AbstractQuantifying RNAs in their spatial context is crucial to understanding gene expression and regulation in complex tissues.In situtranscriptomic methods generate spatially resolved RNA profiles in intact tissues. However, there is a lack of a unified computational framework for integrative analysis ofin situtranscriptomic data. Here, we present an unsupervised and annotation-free framework, termed ClusterMap, which incorporates physical proximity and gene identity of RNAs, formulates the task as a point pattern analysis problem, and thus defines biologically meaningful structures and groups. Specifically, ClusterMap precisely clusters RNAs into subcellular structures, cell bodies, and tissue regions in both two- and three-dimensional space, and consistently performs on diverse tissue types, including mouse brain, placenta, gut, and human cardiac organoids. We demonstrate ClusterMap to be broadly applicable to variousin situtranscriptomic measurements to uncover gene expression patterns, cell-cell interactions, and tissue organization principles from high-dimensional transcriptomic images.
Brain endothelial CXCL12 attracts protective Natural Killer cells during ischemic stroke
Authors: Wang Shuaiwei , de Fabritus Lauriane , Kumar Praveen Ashok , Werner Yves , Siret Carole , Simic Milesa , Kerdiles Yann M. , Stumm Ralf , van de Pavert Serge A. 
Published: February 2021

AbstractInnate lymphoid cells (ILCs) have a function in homeostasis and immune responses, but their role in ischemic brain insult is unknown. Here, we report that ILCs are not resident within the mouse brain parenchyma during steady-state conditions, but are attracted after ischemic stroke. Specifically, we identified NK cells, ILC1s, ILC2s and ILC3s within the lesion, the highest influx being observed for NK cells and ILC1s. We further show that Cxcl12 expressed at the blood-brain barrier is essential for NK cells and NKp46+ILC3s to migrate toward the lesion. Complementary,Cxcr4-deficiency in NK cells prevented NK cells from entering the infarct area. The lack of NK cell migration resulted in a higher neurological deficit in the beam-walk sensorimotor test. Our data show a new role for blood-brain barrier-derived Cxcl12 in attracting protective NK cells to ischemic brain lesions and identifies a new Cxcl12/ Cxcr4-mediated component of the innate immune response to stroke.
Deep Learning-Based Approaches for Decoding Motor Intent from Peripheral Nerve Signals
Authors: Luu Diu Khue , Nguyen Anh Tuan , Jiang Ming , Xu Jian , Drealan Markus W. , Cheng Jonathan , Keefer Edward W. , Zhao Qi , Yang Zhi 
Published: February 2021

AbstractThe ultimate goal of an upper-limb neuroprosthesis is to achieve dexterous and intuitive control of individual fingers. Previous literature shows that deep learning (DL) is an effective tool to decode the motor intent from neural signals obtained from different parts of the nervous system. However, it still requires complicated deep neural networks that are inefficient and not feasible to work in real-time. Here we investigate different approaches to enhance the efficiency of the DL-based motor decoding paradigm. First, a comprehensive collection of feature extraction techniques is applied to reduce the input data dimensionality. Next, we investigate two different strategies for deploying DL models: a one-step (1S) approach when big input data are available and a two-step (2S) when input data are limited. With the 1S approach, a single regression stage predicts the trajectories of all fingers. With the 2S approach, a classification stage identifies the fingers in motion, followed by a regression stage that predicts those active digits’ trajectories. The addition of feature extraction substantially lowers the motor decoder’s complexity, making it feasible for translation to a real-time paradigm. The 1S approach using a recurrent neural network (RNN) generally gives better prediction results than all the ML algorithms with mean squared error (MSE) ranges from 10−3to 10−4for all finger while variance accounted for (VAF) scores are above 0.8 for the most degree of freedom (DOF). This result reaffirms that DL is more advantageous than classic ML methods for handling a large dataset. However, when training on a smaller input data set as in the 2S approach, ML techniques offers a simpler implementation while ensuring comparably good decoding outcome to the DL ones. In the classification step, either machine-learning (ML) or DL models achieve the accuracy and F1 score of 0.99. Thanks to the classification step, in the regression step, both types of models result in comparable MSE and VAF scores as those of the 1S approach. Our study outlines the trade-offs to inform the implementation of real-time, low-latency, and high accuracy DL-based motor decoder for clinical applications.
A Combination Adjuvant for the Induction of Potent Antiviral Immune Responses for a Recombinant SARS-CoV-2 Protein Vaccine
Authors: Jangra Sonia , Landers Jeffrey J. , Rathnasinghe Raveen , O’Konek Jessica J. , Janczak Katarzyna W. , Cascalho Marilia , Kennedy Andrew A. , Tai Andrew W. , Baker James R. , Schotsaert Michael , Wong Pamela T. 
Published: February 2021

AbstractSeveral SARS-CoV-2 vaccines have received EUAs, but many issues remain unresolved, including duration of conferred immunity and breadth of cross-protection. Adjuvants that enhance and shape adaptive immune responses that confer broad protection against SARS-CoV-2 variants will be pivotal for long-term protection. We developed an intranasal, rationally designed adjuvant integrating a nanoemulsion (NE) that activates TLRs and NLRP3 with an RNA agonist of RIG-I (IVT DI). The combination adjuvant with spike protein antigen elicited robust responses to SARS-CoV-2 in mice, with markedly enhanced TH1-biased cellular responses and high virus-neutralizing antibody titers towards both homologous SARS-CoV-2 and a variant harboring the N501Y mutation shared by B1.1.7, B.1.351 and P.1 variants. Furthermore, passive transfer of vaccination-induced antibodies protected naive mice against heterologous viral challenge. NE/IVT DI enables mucosal vaccination, and has the potential to improve the immune profile of a variety of SARS-CoV-2 vaccine candidates to provide effective cross-protection against future drift variants.
MethReg: estimating the regulatory potential of DNA methylation in gene transcription
Authors: Silva Tiago C. , Young Juan I. , Martin Eden R. , Chen Xi , Wang Lily 
Published: February 2021

AbstractEpigenome-wide association studies (EWAS) often detect a large number of differentially methylated sites or regions, many are located in distal regulatory regions. To further prioritize these significant sites, there is a critical need to better understand the functional impact of CpG methylation. Recent studies demonstrated CpG methylation-dependent transcriptional regulation is a widespread phenomenon. Here we present MethReg, an R/Bioconductor package that analyzes matched DNA-methylation and gene-expression data, along with external transcription factor (TF) binding information, to evaluate, prioritize, and annotate CpG sites with high regulatory potential. By simultaneous modeling three key elements that contribute to gene transcription (CpG methylation, target gene expression and TF activity), MethReg identifies TF-target gene associations that are present only in a subset of samples with high (or low) methylation levels at the CpG that influences TF activities, which can be missed in analyses that use all samples. Using real colorectal cancer and Alzheimer’s disease datasets, we show MethReg significantly enhances our understanding of the regulatory roles of DNA methylation in complex diseases.
Ultrastructural analysis of dendritic spine necks reveals a continuum of spine morphologies
Authors: Ofer Netanel , Berger Daniel R. , Kasthuri Narayanan , Lichtman Jeff W. , Yuste Rafael 
Published: February 2021

AbstractDendritic spines are membranous protrusions, with a bulbous head connected to the dendrite by a thin neck, and receive essentially all excitatory inputs in most mammalian neurons. Spines have a wide variety of morphologies that likely have a significant effect on their biochemical and electrical properties. The question of whether spines belong to distinct morphological or functional subtypes or constitute a continuum is still open. To discern this, it is important to measure spine necks objectively. Recent advances in electron microscopy enable automatic reconstructions of 3D spines with nanometer precision. Analyzing ultrastructural reconstructions from mouse neocortical neurons with computer vision algorithms, we demonstrate that the vast majority of spines can be rigorously separated into head and neck components. Analysis of the head and neck morphologies reveals a continuous distribution of parameters. The spine neck diameter, but not the neck length, was correlated with the head volume. Spines with larger head volumes often had a spine apparatus and pairs of spines in a post-synaptic cell contacted by the same axon had similar head volumes. Our data are consistent with a lack of morphological categories of spines and indicate that the morphologies of the spine neck and head are independently regulated. These results have repercussions for our understanding of the function of dendritic spines in neuronal circuits.
Latching dynamics as a basis for short-term recall
Authors: Ryom Kwang Il , Boboeva Vezha , Soldatkina Oleksandra , Treves Alessandro 
Published: February 2021

AbstractWe discuss simple models for the transient storage in short-term memory of cortical patterns of activity, all based on the notion that their recall exploits the natural tendency of the cortex to hop from state to state – latching dynamics. We show that in one such model, and in simple spatial memory tasks we have given to human subjects, short-term memory can be limited to similar low capacity by interference effects, in tasks terminated by errors, and can exhibit similar sublinear scaling, when errors are overlooked. The same mechanism can drive serial recall if combined with weak order-encoding plasticity. Finally, even when storing randomly correlated patterns of activity the network demonstrates correlation-driven latching waves, which are reflected at the outer extremes of pattern space.
Membrane-binding mechanism of the EEA1 FYVE domain revealed by multi-scale molecular dynamics simulations
Authors: Larsen Andreas Haahr , Tata Lilya , John Laura , Sansom Mark S.P. 
Published: February 2021

AbstractEarly Endosomal Antigen 1 (EEA1) is a key protein in endosomal trafficking and is implicated in both autoimmune and neurological diseases. The C-terminal FYVE domain of EEA1 binds endosomal membranes, which contain phosphatidylinositol-3-phosphate (PI(3)P). Although it is known that FYVE binds PI(3)P specifically, it has not previously been described of how FYVE attaches and binds to endosomal membranes. In this study, we employed both coarse-grained (CG) and atomistic (AT) molecular dynamics (MD) simulations to determine how FYVE binds to PI(3)P-containing membranes. CG-MD showed that the dominant membrane binding mode resembles the crystal structure of EEA1 FYVE domain in complex with inositol-1,3-diphospate (PDB ID 1JOC). FYVE, which is a homodimer, binds the membrane via a hinge mechanism, where the C-terminus of one monomer first attaches to the membrane, followed by the C-terminus of the other monomer. The total binding energy is 70 kJ/mol, of which 50-60 kJ/mol stems from specific PI(3)P-interactions. By AT-MD, we could partition the binding mode into two types: (i) adhesion by electrostatic FYVE-PI(3)P interaction, and (ii) insertion of amphipathic loops. The AT simulations also demonstrated flexibility within the FYVE homodimer between the C-terminal heads and coiled-coil stem, allowing binding via a mechanism resembling that of a suction cup connected to a locally rigid stem via a flexible hinge.
Muscle-specific economy of force generation and efficiency of work production during human running
Authors: Bohm Sebastian , Mersmann Falk , Santuz Alessandro , Schroll Arno , Arampatzis Adamantios 
Published: February 2021

AbstractHuman running features a spring-like interaction of body and ground, enabled by elastic tendons that store mechanical energy and facilitate muscle operating conditions to minimize the metabolic cost. By experimentally assessing the operating conditions of two important muscles for running, the soleus and vastus lateralis, we investigated physiological mechanisms of muscle energy production and muscle force generation. Results showed that the soleus continuously shortened throughout the stance phase, operating as energy generator under conditions that were found to be optimal for work production: high force-length potential and enthalpy efficiency. The vastus lateralis promoted tendon energy storage and contracted nearly isometrically close to optimal length, resulting in a high force-length-velocity potential beneficial for economical force generation. The favorable operating conditions of both muscles were a result of an effective length and velocity-decoupling of fascicles and muscle-tendon unit mostly due to tendon compliance and, in the soleus, marginally by fascicle rotation.
ChEC-seq: a robust method to identify protein-DNA interactions genome-wide
Authors: Bruzzone Maria Jessica , Albert Benjamin , Hafner Lukas , Kubik Slawomir , Lezaja Aleksandra , Mattarocci Stefano , Shore David 
Published: February 2021

AbstractMittal et al. (2021; first brought to our attention in May 2019) have raised concerns regarding the Chromatin Endogenous Cleavage-sequencing (ChEC-seq) technique (Zentner et al., 2015) that may create a false impression that this method has fundamental flaws which prevent one from distinguishing between signal and noise. Although Mittal et al. focus on studies of the global co-activators SAGA, TFIID and Mediator that we were not involved in, we feel obliged to highlight here several of our own publications (Albert et al., 2019; Bruzzone et al., 2018; Hafner et al., 2018; Kubik et al., 2019; Kubik et al., 2018), as well as recent unpublished data, that employed ChEC-seq and directly addressed the observation raised by Mittal et al. that cleavage maps for various MNase fusion proteins often qualitatively resemble each other and those generated by “free” (unfused) MNase. Our studies lay out a clear path for determining sites of preferential factor localization by normalization of ChEC-seq experimental data to matched free-MNase controls. They also demonstrate the use of in vivo functional assays to assess ChEC-seq reliability and reveal examples where ChEC-seq identifies functional binding sites missed by conventional ChIP-seq analysis.
So you want to be a Super Researcher
Authors: Rathee Sanjay , Lee Sheah Lin 
Published: February 2021

AbstractPublishing original scientific research is inherent to the work of a researcher. However, the pressure to maintain productivity and scientific impact can lead to research group publishing excessively, negatively affecting the mental health of a researcher. Ph.D. students and early career researchers are particularly susceptible to this pressure due to the inherent vulnerability of their positions. At present, there are no resources that concisely summarise the publication culture of a research group to help the researcher make an informed decision before joining. In this article, we present the ‘Super Researcher’ app, an R Shiny application(app) with a user-friendly interface. Using text-mining methodology to extract publicly available author data from Scopus, this pilot app has four fundamental functions to provide snapshot information that will help researchers grasp the publication culture of a research group within minutes. The ‘Super Researcher’ app provides information on: 1) institution data, 2) author’s publication, 3) co-author network plots and 4) publication journals.The ‘Super Researcher’ app is built on R shiny which provides an interactive interface to users. This app utilizes the Big Data framework Apache Spark to mine relevant information from a huge author information database. The author’s information is stored and manipulated using both SQL(SQLite) and NoSQL(HBase) databases. Hbase is used for local data storage and manipulation while SQLite feeds data to the R Shiny interface.In this paper, we introduce these functionalities and illustrate how this information can help guide a researcher to select a new Principle Investigator (PI) with better compatibility in terms of publication attitude using a case study. Available:https://researchmind.co.uk/super-researcher/
Rotavirus susceptibility of antibiotic-treated mice ascribed to diminished expression of interleukin-22
Authors: Schnepf Daniel , Hernandez Pedro , Mahlakõiv Tanel , Crotta Stefania , Sullender Meagan E. , Peterson Stefan T. , Ohnemus Annette , Michiels Camille , Gentle Ian , Dumoutier Laure , Reis Celso A. , Diefenbach Andreas , Wack Andreas , Baldridge Megan T. , Staeheli Peter 
Published: February 2021

AbstractThe commensal microbiota regulates susceptibility to enteric pathogens by fine-tuning mucosal innate immune responses, but how susceptibility to enteric viruses is shaped by the microbiota remains incompletely understood. Past reports have indicated that commensal bacteria may either promote or repress rotavirus replication in the small intestine of mice. We now report that rotavirus replicated more efficiently in the intestines of germ-free and antibiotic-treated mice compared to animals with an unmodified microbiota. Antibiotic treatment also facilitated rotavirus replication in type I and type III interferon (IFN) receptor-deficient mice, revealing IFN-independent proviral effects. Expression of interleukin-22 (IL-22) was strongly diminished in the intestine of antibiotic-treated mice. Treatment with exogenous IL-22 blocked rotavirus replication in microbiota-depleted wild-type andStat1-/-mice, demonstrating that the antiviral effect of IL-22 in animals with altered microbiome is not dependent on IFN signaling. In antibiotic-treated animals, IL-22-induced a specific set of genes includingFut2, encoding fucosyl-transferase 2 that participates in the biosynthesis of fucosylated glycans which can mediate rotavirus binding. Interestingly, IL-22 also blocked rotavirus replication in antibiotic-treatedFut2-/-mice. Furthermore, IL-22 inhibited rotavirus replication in antibiotic-treated mice lacking key molecules of the necroptosis or pyroptosis pathways of programmed cell death. Taken together, our results demonstrate that IL-22 determines rotavirus susceptibility of antibiotic-treated mice, yet the IL-22-induced effector molecules conferring rotavirus resistance remain elusive.