bluuebunny/crossref_metadata_2025_split huggingface dataset:
Platelet polyphosphate and SARS-Cov-2 mRNA-vaccine-induced inflammatory side effects: a pilot study
Authors: Uematsu Takashi , Sato Atsushi , Aizawa Hachidai , Tsujino Tetsuhiro , Watanabe Taisuke , Isobe Kazushige , Kawabata Hideo , Kitamura Yutaka , Tanaka Takaaki , Kawase Tomoyuki 
Published: September 2021

AbstractBackgroundPlatelets have recently been recognized as immune cells. Platelets first contact invading pathogens and then induce immune reactions in cooperation with white blood cells. Platelet polyphosphate (polyP), which is classically recognized as a thrombotic and hemostatic biomolecule, has recently attracted attention as a ‘cytokine’ that modulates inflammation and is involved in intercellular communication between platelets and major immune cells.ObjectiveTo determine the involvement of polyP in SARS-Cov-2-mRNA vaccine-induced immune responses, this pilot study examined the effects of mRNA vaccines on platelet polyP levels.MethodsBefore and after vaccination (BNT162b2), blood samples were obtained from healthy, non-smoking individuals (relatively older male group, n=6 vs. younger female group, n=23), who did not have systemic diseases that required continuous treatment. Washed platelets were prepared and subjected to a fluorometric determination of platelet polyP levels using 4’,6-diamidino-2-phenylindole. The side effects of vaccination were recorded as scores.ResultsCompared with the male group, platelet polyP levels decreased in the relatively younger female group after the initial dose, while the side effect score increased in the female group after the second dose. Moderate correlation coefficients were observed between the reduction in polyP levels and the side effect scores or the original polyP levels.ConclusionsDespite being a pilot study using a small sample size, this study suggests the possibility that platelet polyP may suppress the side effects induced by the mRNA vaccines after the initial dose, but not the second dose, in relatively young female subjects who generally have high immune responsiveness.EssentialsThe COVID-19 mRNA vaccines (BNT162b2) reduced platelet polyP levels after the initial dose, but not after the 2nddose, in relatively younger female subjects.Relatively older male subjects did not respond to the vaccination by reducing platelet polyP.These findings suggest that platelets release polyP to suppress vaccine-induced reactions, for example, inflammation, which is usually recognized as a side effect.However, such suppression could be observed in subjects with higher immune responses, generally in relatively younger female subjects.
Social Capital Dimensions are Differentially Associated with COVID-19 Vaccinations, Masks, and Physical Distancing *
Authors: Ferwana Ibtihal , Varshney Lav R. 
Published: September 2021

AbstractBackgroundSocial capital has been associated with health outcomes in communities and can explain variations in different geographic localities. Social capital has also been associated with behaviors that promote better health and reduce the impacts of diseases. During the COVID-19 pandemic, social distancing, face masking, and vaccination have all been essential in controlling contagion. These behaviors have not been uniformly adopted by communities in the United States. Using different facets of social capital to explain the differences in public behaviors among communities during pandemics is lacking.ObjectiveThis study examines the relationship among public health behavior—vaccination, face masking, and physical distancing—during COVID-19 pandemic and social capital indices in counties in the United States.MethodsWe used publicly available vaccination data as of June 2021, face masking data in July 2020, and mobility data from mobile phones movements from the end of March 2020. Then, correlation analysis was conducted with county-level social capital index and its subindices (family unity, community health, institutional health, and collective efficacy) that were obtained from the Social Capital Project by the United States Senate.ResultsWe found the social capital index and its subindices differentially correlate with different public health behaviors. Vaccination is associated with institutional health: positively with fully vaccinated population and negatively with vaccination hesitancy. Also, wearing masks negatively associates with community health, whereases reduced mobility associates with better community health. Further, residential mobility positively associates with family unity. By comparing correlation coefficients, we find that social capital and its subindices have largest effect sizes on vaccination and residential mobility.ConclusionOur results show that different facets of social capital are significantly associated with adoption of protective behaviors, e.g., social distancing, face masking, and vaccination. As such, our results suggest that differential facets of social capital imply a Swiss cheese model of pandemic control planning where, e.g., institutional health and community health, provide partially overlapping behavioral benefits.
MetaTrass: High-quality metagenome assembly on the human gut microbiome by co-barcoding sequencing reads
Authors: Qi Yanwei , Gu Shengqiang , Zhang Yue , Guo Lidong , Xu Mengyang , Cheng Xiaofang , Wang Ou , Chen Jianwei , Fang Xiaodong , Liu Xin , Deng Li , Fan Guangyi 
Published: September 2021

AbstractWith the development of sequencing technologies and computational analysis in metagenomics, the genetic diversity of non-conserved regions has been receiving intensive attention to unravel the human gut microbial community. However, it remains a challenge to obtain enough microbial draft genomes at a high resolution from a single sample. In this work, we presented MetaTrass with a strategy of binning first and assembling later to assemble high-quality draft genomes based on metagenomics co-barcoding reads and the public reference genomes. We applied the tool to the single tube long fragment reads datasets for four human faecal samples, and generated more high-quality draft genomes with longer contiguity and higher resolution than the common combination strategies of genome assembling and binning. A total of 178 high-quality genomes was successfully assembled by MetaTrass, but the maximum of 58 was generated by the optimal common combination strategy in our tests. These high-quality genomes paved the way for genetic diversity and lineage analysis among different samples. With the high capability of assembling high-quality genomes of metagenomics datasets, MetaTrass will facilitate the study of spatial characters and dynamics of complex microbial communities at high resolution. The open-source code of MetaTrass is available at https://github.com/BGI-Qingdao/MetaTrass.
In Silico Epitope Prediction And VP1 Modelling For Foot-And-Mouth Serotype SAT 2 For Vaccine Design In East Africa
Authors: Udahemuka Jean Claude , Accadius Lunayo , Obiero George , Aboge Gabriel , Lebea Phiyani 
Published: September 2021

AbstractFoot and Mouth Disease Virus has seven distinct, geographically localized, serotypes and a vaccination targeting one serotype does not confer immunity against another serotype. The use of inactivated vaccines is not safe and confers an immunity with a relatively shorter time. Using the VP1 sequences isolated in East Africa, we have predicted epitopes able to induce humoral and cell-mediated immunity in cattle. The Wu-Kabat variability index calculated in this study reflects the variable, including the known GH loop, and conserved regions, with the latter being good candidates for region-tailored vaccine design. Furthermore, we modelled the identified epitopes on a 3D model (PDB ID:5aca) to represent the epitopes structurally. This study can be used for in vitro and in vivo experiments.
Confronting population models with experimental microcosm data: from trajectory matching to state-space models
Authors: Rosenbaum Benjamin , Fronhofer Emanuel A. 
Published: September 2021

AbstractPopulation and community ecology traditionally has a very strong theoretical foundation with well-known dynamical models, such as the logistic and its variations, and many modification of the classical Lotka-Volterra predator-prey and interspecific competition models. More and more, these classical models are being confronted with data via fitting to empirical time series for purposes of projections or for estimating model parameters of interest. However, using statistical models to fit theoretical models to data is far from trivial, especially for time series data where subsequent measurements are not independent. This raises the question of whether statistical inferences using pure observation error models, such as simple (non-)linear regressions, are biased, and whether more elaborate process error models or state-space models have to be used to address this complexity.In order to help empiricists, especially researchers working with experimental laboratory populations in micro- and mesocosms, make informed decisions about the statistical formalism to use, we here compare different error structures one could use when fitting classical deterministic ODE models to empirical data. We consider a large range of biological scenarios and theoretical models, from single species to community dynamics and trophic interactions. In order to compare the performance of different error structure models, we use both realistically simulated data and empirical data from microcosms in a Bayesian framework.We find that many model parameters can be estimated precisely with an appropriate choice of error structure using pure observation error or state-space models, if observation errors are not too high. However, Allee effect models are typically hard to identify and state-space models should be preferred when model complexity increases.Our work shows that, at least in the context of low environmental stochasticity and high quality observations, deterministic models can be used to describe stochastic population dynamics that include process variability and observation error. We discuss when more complex state-space model formulations may be required for obtaining accurate parameter estimates. Finally, we provide a comprehensive tutorial for fitting these models in R.Open researchCode for stochastic individual-based simulations is available fromhttps://doi.org/10.5281/zenodo.5500442. A tutorial for fitting ODE models to time series data in R is presented in the Supplementary Information and is also available onlinehttps://github.com/benjamin-rosenbaum/fittingdeterministic population models. Data (Fronhofer et al., 2020) will be provided via GitHub and Zenodo.
Predictors of human-infective RNA virus discovery in the United States, China and Africa, an ecological study
Authors: Zhang Feifei , Chase-Topping Margo , Guo Chuan-Guo , Woolhouse Mark E.J. 
Published: September 2021

AbstractBackgroundThe variation in the pathogen type as well as the spatial heterogeneity of predictors make the generality of any associations with pathogen discovery debatable. Our previous work confirmed that the association of a group of predictors differed across different types of RNA viruses, yet there have been no previous comparisons of the specific predictors for RNA virus discovery in different regions. The aim of the current study was to close the gap by investigating whether predictors of discovery rates within three regions—the United States, China and Africa—differ from one another and from those at the global level.MethodsBased on a comprehensive list of human-infective RNA viruses, we collated published data on first discovery of each species in each region. We used a Poisson boosted regression tree (BRT) model to examine the relationship between virus discovery and 33 predictors representing climate, socio-economics, land use, and biodiversity across each region separately. The discovery probability in three regions in 2010–2019 was mapped using the fitted models and historical predictors.ResultsThe numbers of human-infective virus species discovered in the United States, China and Africa up to 2019 were 95, 80 and 107 respectively, with China lagging behind the other two regions. In each region, discoveries were clustered in hotspots. BRT modelling suggested that in all three regions RNA virus discovery was best predicted by land use and socio- economic variables, followed by climatic variables and biodiversity, though the relative importance of these predictors varied by region. Map of virus discovery probability in 2010– 2019 indicated several new hotspots outside historical high-risk areas. Most new virus species since 2010 in each region (6/6 in the United States, 19/19 in China, 12/19 in Africa) were discovered in high risk areas as predicted by our model.ConclusionsThe drivers of spatiotemporal variation in virus discovery rates vary in different regions of the world. Within regions virus discovery is driven mainly by land-use and socio- economic variables; climate and biodiversity variables are consistently less important predictors than at a global scale. Potential new discovery hotspots in 2010–2019 are identified. Results from the study could guide active surveillance for new human-infective viruses in local high risk areas.FundingDarwin Trust of Edinburgh; European Union.
Mapping brain-wide excitatory projectome of primate prefrontal cortex at submicron resolution: relevance to diffusion tractography
Authors: Yan Mingchao , Yu Wenwen , Lv Qian , Lv Qiming , Bo Tingting , Chen Xiaoyu , Liu Yilin , Zhan Yafeng , Yan Shengyao , Shen Xiangyu , Yang Baofeng , Qiu Zilong , Feng Yuanjing , Zhang Xiaoyong , Wang He , Xu Fuqiang , Wang Zheng 
Published: September 2021

AbstractResolving trajectories of axonal pathways in the primate prefrontal cortex remains crucial to gain insights into higher-order processes of cognition and emotion, which requires a comprehensive map of axonal projections linking demarcated subdivisions of prefrontal cortex and the rest of brain. Here we report a mesoscale excitatory projectome issued from the ventrolateral prefrontal cortex (vlPFC) to the entire macaque brain by using viral-based genetic axonal tracing in tandem with high-throughput serial two-photon tomography, which demonstrated prominent monosynaptic projections to other prefrontal areas, temporal, limbic and subcortical areas, relatively weak projections to parietal and insular cortices but no projections directly to the occipital lobe. In a common 3D space, we quantitatively validated an atlas of diffusion tractography-derived vlPFC connections with correlative enhanced green fluorescent protein-labelled axonal tracing, and observed generally good agreement except a major difference in the posterior projections of inferior fronto-occipital fasciculus. These findings raise an intriguing question as to how neural information passes along long-range association fiber bundles in macaque brains, and call for the caution of using diffusion tractography to map the wiring diagram of brain circuits.
DNA metabarcoding reveals host-specific communities of arthropods residing in fungal fruit bodies
Authors: Lunde Lisa Fagerli , Birkemoe Tone , Kauserud Håvard , Boddy Lynne , Jacobsen Rannveig M. , Sverdrup-Thygeson Anne , Maurice Sundy 
Published: September 2021

AbstractBiological communities within living organisms are structured by their host’s traits. How host traits affect biodiversity and community composition is poorly explored for some associations, such as arthropods within fungal fruit bodies. Using DNA metabarcoding, we revealed the arthropod communities in living fruit bodies of eleven wood-decay fungi from boreal forests and investigated how they were affected by different fungal traits. Arthropod diversity was higher in fruit bodies with a larger surface area-to-volume ratio, suggesting that colonisation is crucial to maintain arthropod populations. Diversity was not higher in long-lived fruit bodies, most likely because these fungi invest in physical or chemical defences against arthropods. Arthropod community composition was structured by all measured host traits, namely fruit body size, thickness, surface area, morphology and toughness. Notably, we identified a community gradient where soft and short-lived fruit bodies harboured more true flies, while tougher and long-lived fruit bodies had more oribatid mites and beetles, which might reflect different development times of the arthropods. Ultimately, close to 75% of the arthropods were specific to one or two fungal hosts. Besides revealing surprisingly diverse and host-specific arthropod communities within fungal fruit bodies, our study provided insight on how host traits structure communities.
Convex-PLR – Revisiting affinity predictions and virtual screening using physics-informed machine learning
Authors: Kadukova Maria , Chupin Vladimir , Grudinin Sergei 
Published: September 2021

AbstractVirtual screening is an essential part of the modern drug design pipeline, which significantly accelerates the discovery of new drug candidates. Structure-based virtual screening involves ligand conformational sampling, which is often followed by re-scoring of docking poses. A great variety of scoring functions have been designed for this purpose. The advent of structural and affinity databases and the progress in machine-learning methods have recently boosted scoring function performance. Nonetheless, the most successful scoring functions are typically designed for specific tasks or systems. All-purpose scoring functions still perform poorly on the virtual screening tests, compared to precision with which they are able to predict co-crystal binding poses. Another limitation is the low interpretability of the heuristics being used.We analyzed scoring functions’ performance in the CASF benchmarks and discovered that the vast majority of them have a strong bias towards predicting larger binding interfaces. This motivated us to develop a physical model with additional entropic terms with the aim of penalizing such a preference. We parameterized the new model using affinity and structural data, solving a classification problem followed by regression. The new model, called Convex-PLR, demonstrated high-quality results on multiple tests and a substantial improvement over its predecessor Convex-PL. Convex-PLR can be used for molecular docking together with VinaCPL, our version of AutoDock Vina, with Convex-PL integrated as a scoring function. Convex-PLR, Convex-PL, and VinaCPL are available at https://team.inria.fr/nano-d/convex-pl/.
Addition of a carboxy terminal tail to the normally tailless gonadotropin-releasing hormone receptor impairs fertility in female mice
Authors: Toufaily Chirine , Fortin Jérôme , Alonso Carlos A. I. , Lapointe Evelyn , Zhou Xiang , Santiago-Andres Yorgui , Lin Yeu-Farn , Cui Yimming , Wang Ying , Devost Dominic , Roelfsema Ferdinand , Steyn Frederik , Hanyaloglu Aylin C. , Hébert Terence E. , Fiordelisio Tatiana , Boerboom Derek , Bernard Daniel J. 
Published: September 2021

ABSTRACTGonadotropin-releasing hormone (GnRH) is the primary neuropeptide controlling reproduction in vertebrates. GnRH stimulates follicle-stimulating hormone (FSH) and luteinizing hormone (LH) synthesis via a G protein-coupled receptor, GnRHR, in the pituitary gland. In mammals, GnRHR lacks a C-terminal cytosolic tail (Ctail) and does not exhibit homologous desensitization. This might be an evolutionary adaptation that enables LH surge generation and ovulation. To test this idea, we fused the chicken GnRHR Ctail to the endogenous murine GnRHR in a transgenic model. The LH surge was blunted, but not blocked in these mice. In contrast, they showed reductions in FSH production, ovarian follicle development, and fertility. Addition of the Ctail altered the nature of agonist-induced calcium signaling required for normal FSH production. The loss of the GnRHR Ctail during mammalian evolution is unlikely to have conferred a selective advantage by enabling the LH surge. The adaptive significance of this specialization remains to be determined.
Population dynamics of Amazonian floodplain forest species support spatial variation on genetic diversity but not range expansions through time
Authors: Thom Gregory , Ribas Camila C. , Shultz Eduardo , Aleixo Alexandre , Miyaki Cristina Y. 
Published: September 2021

AbstractAimWe tested if historical demographic changes of populations occurring on the floodplains of a major Amazon Basin tributary could be associated with range expansions from upper and middle sections of the river, following the establishment of widespread river-created environments during the Late Pleistocene and Holocene.LocationSolimoes River, Western Amazon, South AmericaTaxonMyrmoborus lugubris, Thamnophilus cryptoleucus and Myrmotherula assimilisMethods: We analyzed thousands of UltraConserved Elements to explore spatial patterns of genetic diversity and connectivity between individuals. Range expansions were tested with alternative methods. We quantified habitat preference for the analyzed species in order to test if the occupation of dynamic habitats could predict spatial patterns of genetic diversity.ResultsOur study did not support shared population range expansions related to historical regionalized changes in habitat availability. We found considerable variation in the spatial distribution of the genetic diversity between studied taxa, and that species with higher levels of specialization to dynamic environments have a more heterogeneous distribution of genetic diversity and reduced levels of gene flow across space.Main conclusionsOur results suggest that demographic expansions along the Solimões River might be linked to geographic homogeneous oscillation in the distribution of floodplain environments, promoting effective population size changes but not range expansion. We found that habitat specificity might be a good predictor of population connectivity along the Amazonian floodplains.
The conventional dendritic cell 1 subset primes CD8+ T cells and traffics tumor antigen to drive anti-tumor immunity in the brain
Authors: Bowman-Kirigin Jay A. , Saunders Brian T. , Desai Rupen , Wang Anthony Z. , Schaettler Max O. , Liu Connor J. , Livingstone Alexandra J. , Kobayashi Dale K. , Durai Vivek , Kretzer Nicole M. , Zipfel Gregory J. , Leuthardt Eric C. , Osbun Joshua W. , Chicoine Michael R. , Kim Albert H. , Murphy Kenneth M. , Johanns Tanner M. , Zinselmeyer Bernd H. , Dunn Gavin P. 
Published: September 2021

AbstractThe central nervous system (CNS) antigen presenting cell (APC) which primes anti-tumor CD8+ T cell responses remains undefined. Elsewhere, the conventional dendritic cell 1 (cDC1) performs this role. However, steady-state brain cDC1 are rare; cDC localize to choroid plexus and dura. Using preclinical glioblastoma models and cDC1-deficient mice, we explored the role of cDC1 in CNS anti-tumor immunity. We determined that cDC1 mediate checkpoint blockade-induced survival benefit and prime neoantigen-specific CD8+ T cells against brain tumors. We observed that cDC, including cDC1, isolated from the tumor, the dura, and the CNS-draining cervical lymph nodes harbored a traceable fluorescent tumor-antigen. In patient samples, we observed several APC subsets (including the CD141+ cDC1-equivalent) infiltrating glioblastomas, meningiomas, and dura. In these same subsets, we identified a tumor-specific fluorescent metabolite of 5- aminolevulinic acid, which labels tumor cells during fluorescence-guided glioblastoma resection. Together, these data elucidate the specialized behavior of cDC1 and suggest cDC1 play a significant role in CNS anti-tumor immunity.One Sentence SummaryCNS cDC1 engage in previously undefined behavior to establish immune responses against brain tumors.