bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neutrophils cause critical illness in COVID-19 and reveal CDK6 inhibitors as potential treatment
Authors: Baukmann Hannes A. , Cope Justin L. , Ravarani Charles N. J. , Bannard Colin , Lamparter Margaretha R. J. , Schwinges Alexander R. E. C. , Klinger Joern E. , Schmidt Marco F. 
Published: May 2021

AbstractBackgroundDespite recent development of vaccines and monoclonal antibodies to prevent SARS-CoV-2 infection, treatment of critically ill COVID-19 patients remains an important goal. In principle, genome-wide association studies (GWAS) could shortcut the clinical evidence needed to repurpose drugs - the use of an existing drug for a new indication. However, it has been shown that the genes found in GWA studies usually do not encode an established drug target and the causal role for disease, a key requirement for drug efficacy, is unclear. We report here an alternative method for finding and testing causal target candidates for drug repurposing.MethodsRather than focusing on the genetics of the disease, we looked for disease-causing traits by searching for significant differences in 33 blood cell types, 30 blood biochemistries, and body mass index between an infectious disease phenotype and healthy controls. We then matched critically ill COVID-19 cases with controls that exhibited mild or no symptoms after SARS-CoV-2 infection in order to identify disease-causing traits by applying causal inference methods.ResultsWe found high neutrophil cell count as a causal trait for the immune overreaction in critical illness due to COVID-19. Based on these findings, we identified the enzyme CDK6 as a potential drug target to prevent the immune overreaction in critical illness due to COVID-19.ConclusionsThe genetics of disease-causing traits turns out to be a rich reservoir for the identification of known drug targets. This is due to the usually larger datasets of traits, as they also cover healthy ones. A clinical trial testing CDK6 inhibitor palbociclib in critically ill COVID-19 patients is currently ongoing (ClinicalTrials.gov Identifier: NCT05371275).
Can alcohol consumption in Germany be reduced by alcohol screening, brief intervention and referral to treatment in primary health care? Results of a simulation study
Authors: Manthey Jakob , Solovei Adriana , Anderson Peter , Carr Sinclair , Rehm Jürgen 
Published: May 2021

AbstractBackgroundScreening, brief intervention and referral to treatment (SBIRT) is a programme to reduce alcohol consumption for drinkers with high alcohol consumption levels. Only 2.9% of patients in primary health care (PHC) are screened for their alcohol use in Germany, despite high levels of alcohol consumption and attributable harm. We developed an open-access simulation model to estimate the impact of higher SBIRT delivery rates in German PHC settings on population-level alcohol consumption.Methods and findingsA hypothetical population of drinkers and non-drinkers was simulated by sex, age, and educational status for the year 2009 based on survey and sales data. Risky drinking persons receiving BI or RT were sampled from this population based on screening coverage and other parameters. Running the simulation model for a ten-year period, drinking levels and heavy episodic drinking (HED) status were changed based on effect sizes from meta-analyses.In the baseline scenario of 2.9% screening coverage, 2.4% of the adult German population received a subsequent intervention between 2009 and 2018. If every second PHC patient would have been screened for alcohol use, 21% of adult residents in Germany would have received BI or RT by the end of the ten-year simulation period. In this scenario, population-level alcohol consumption would be 12% lower than it was in 2018, without any impact on HED prevalence. Screening coverage rates below 10% were not found to have a measurable effect on drinking levels.ConclusionsLarge-scale implementation of SBIRT in PHC settings can yield substantial reductions of alcohol consumption in Germany. As high screening coverage rates may only be achievable in the long run, other effective alcohol policies are required to achieve short-term reduction of alcohol use and attributable harm in Germany. There is large potential to apply this open-access simulation model to other settings and for other alcohol interventions.
Integrating Health Behavior Theories to Predict COVID-19 Vaccine Acceptance: Differences between Medical Students and Nursing Students
Authors: Rosental Hila , Shmueli Liora 
Published: May 2021

AbstractBackgroundThis study aimed to explore behavioral-related factors predicting the intention of getting a COVID-19 vaccine among medical and nursing students using an integrative model combining the Health Belief Model (HBM) and the Theory of Planned Behavior (TPB).MethodsA cross-sectional online survey was conducted among medical and nursing students aged > 18 years in their clinical years in Israel between 27 August and 28 September 2020. Hierarchical logistic regression was used to predict acceptance of a COVID-19 vaccine.ResultsA total number of 628 participants completed the survey. Medical students expressed higher intentions of getting vaccinated against COVID-19 than nursing students (88.1% vs. 76.2%, p < 0.01). The integrated model based on HBM and TPB was able to explain 66% of the variance (adjusted R2 = 0.66). Participants were more likely to be willing to get vaccinated if they reported higher levels of perceived susceptibility, benefits, barriers, cues to action, attitude, self-efficacy and anticipated regret. Two interaction effects revealed that male nurses had a higher intention of getting vaccinated than did female nurses and that susceptibility is a predictor of the intention of getting vaccinated only among nurses.ConclusionsThis study demonstrates that both models considered (i.e., HBM and TPB) are important for predicting the intention of getting a COVID-19 vaccine among medical and nursing students, and can help better guide intervention programs, based on components from both models. Our findings also highlight the importance of paying attention to a targeted group of female nurses, who expressed low vaccine acceptance.
In pursuit of a better broiler: A comparison of the inactivity, behavior, and enrichment use of fast- and slower-growing broiler chickens
Authors: Dawson Lauren C. , Widowski Tina M. , Liu Zhenzhen , Edwards A. Michelle , Torrey Stephanie 
Published: May 2021

ABSTRACTSelection for rapid growth has produced heavier, more efficient broiler chickens, but has also introduced health and welfare issues, which may cause or be caused by inactivity. Rapid growth may also limit the performance of motivated behaviors, whereas the provision of enrichment may increase these behaviors and general activity. This study aimed to evaluate the inactivity, behavior, and enrichment use of 2 fast- (CONV) and 12 slower-growing broiler strains [categorized as fastest (FAST), moderate (MOD) and slowest slow (SLOW), based on their growth rates]. To evaluate inactivity, one male and one female from 153 pens were outfitted with omni-directional accelerometers from day 21 until processing (14–24 birds/strain from 8-12 pens/strain). Additionally, to supplement inactivity data, five-minute continuous behavioral observations of four focal birds per pen (2 males, 2 females) were conducted on days 26, 42, and 56 (72–148 observations of 8–12 pens/strain) to quantify the duration and frequency of various behaviors; at the same time, 5–11 instantaneous scan samples were also performed for pen-based enrichment use. Inactivity peaked at 78-80% of the day for all strains; however, those with slower growth rates reached these levels at older ages. Compared to slower-growing strains at the same age, faster-growing strains were more inactive, spent more time sitting and feeding, spent less time standing and walking, and used enrichments less; these differences mostly occurred at younger ages. Generally, at the same age, strains with similar growth rates (within the same category) behaved similarly, with only a few exceptions. Results suggest that not all strains identified as ‘slow-growing’ broilers behave differently from fast-growing broilers, nor do they all behave similarly to each other. As such, results suggest that improved broiler welfare, particularly with respect to reduced inactivity, the performance of a wider range of normal, motivated behaviors, and/or increased enrichment use, is related to the broiler strain’s specific growth rate.
Multiframe Evolving Dynamic Functional Connectivity (EVOdFNC): A Method for Constructing and Investigating Functional Brain Motifs
Authors: Miller Robyn L. , Vergara Victor M. , Pearlson Godfrey , Calhoun Vince D. 
Published: May 2021

ABSTRACTThe study of brain network connectivity as a time-varying property began relatively recently and to date has remained primarily concerned with capturing a handful of discrete static states that characterize connectivity as measured on a timescale shorter than that of the full scan. Capturing group-level representations of temporally evolving patterns of connectivity is a challenging and important next step in fully leveraging the information available in large resting state functional magnetic resonance imaging (rs-fMRI) studies. We introduce a flexible, extensible data-driven framework for the stable identification of group-level multiframe (movie-style) dynamic functional network connectivity (dFNC) states. Our approach employs uniform manifold approximation and embedding (UMAP) to produce a continuity-preserving planar embedding of high-dimensional time-varying measurements of whole-brain functional network connectivity. Planar linear exemplars summarizing dominant dynamic trends across the population are computed from local linear approximations to the 2D embedded trajectories. A high-dimensional representation of each 2D exemplar segment is obtained by averaging the dFNC observations corresponding to the n planar nearest neighbors of τ evenly spaced points along the 2D line segment representation (where n is the UMAP number-of-neighbors parameter and τ is the temporal duration of trajectory segments being approximated). Each of the 2D exemplars thus “lifts” to a multiframe high-dimensional dFNC trajectory of length τ. The collection of high-dimensional temporally evolving dFNC representations (EVOdFNCs) derived in this manner are employed as dynamic basis objects with which to characterize observed high-dimensional dFNC trajectories, which are then expressed as weighted combination of these basis objects. Our approach yields new insights into anomalous patterns of fluidly varying whole brain connectivity that are significantly associated with schizophrenia as a broad diagnosis as well as with certain symptoms of this serious disorder. Importantly, we show that relative to conventional hidden Markov modeling with single-frame unvarying dFNC summary states, EVOdFNCs are more sensitive to positive symptoms of schizophrenia including hallucinations and delusions, suggesting a more dynamic characterization is needed to help illuminate such a complex brain disorder.
A METHOD FOR INTEGRATIVE ANALYSIS OF LOCAL AND GLOBAL BRAIN DYNAMICS
Authors: Miller Robyn L. , Vergara Victor M. , Calhoun Vince D. 
Published: May 2021

ABSTRACTThe most common pipelines for studying time-varying network connectivity in resting state functional magnetic resonance imaging (rs-fMRI) operate at the whole brain level, capturing a small discrete set of “states” that best represent time-resolved joint measures of connectivity over all network pairs in the brain. This whole-brain hidden Markov model (HMM) approach “uniformizes” the dynamics over what is typically more than 1000 pairs of networks, forcing each time-resolved high-dimensional observation into its best-matched high-dimensional state. While straightforward and convenient, this HMM simplification obscures functional and temporal nonstationarities that could reveal systematic, informative features of resting state brain dynamics at a more granular scale. We introduce a framework for studying functionally localized dynamics that intrinsically embeds them within a whole-brain HMM frame of reference. The approach is validated in a large rs-fMRI schizophrenia study where it identifies group differences in localized patterns of entropy and dynamics that help explain consistently observed differences between schizophrenia patients and controls in occupancy of whole-brain dFNC states more mechanistically.
Zika virus noncoding RNA cooperates with the viral protein NS5 to inhibit STAT1 phosphorylation and facilitate viral pathogenesis
Authors: Slonchak Andrii , Wang Xiaohui , Chaggar Harman , Aguado Julio , Freney Morgan , Yan Kexin , Torres Francisco J , Amarilla Alberto A , Balea Rickyle , Sng Julian D. J. , Setoh Yin Xiang , Peng Nias , Watterson Daniel , Wolvetang Ernst , Suhrbier Andreas , Khromykh Alexander A 
Published: May 2021

AbstractZika virus (ZIKV) is a re-emerging pathogenic flavivirus, which causes microcephaly in infants and poses a continuing threat to public health. ZIKV, like all other flaviviruses, produces highly abundant noncoding RNA known as subgenomic flaviviral RNA (sfRNA). Herein we utilized wild-type and mutant ZIKV defective in production of sfRNA to elucidate for the first time how production of sfRNA affects all aspects of ZIKV pathogenesis. We found that in mouse pregnancy model of infection sfRNA is required for trans-placental dissemination of ZIKV and subsequent infection of fetal brain. Using human brain organoids, we showed that sfRNA promotes apoptosis of neural progenitor cells leading to profound cytopathicity and disintegration of organoids. We also found by transcriptome profiling and gene network analysis that in infected human placental cells sfRNA inhibits multiple antiviral pathways and promotes apoptosis with STAT1 identified as a key shared factor linking these two interconnected sfRNA activities. We further showed for the first time that sfRNA inhibits phosphorylation and nuclear translocation of STAT1 by a novel mechanism which involves binding to and stabilizing viral protein NS5. This allows accumulation of NS5 at the levels required for efficient inhibition of STAT1 phosphorylation. Thus, we elucidated the molecular mechanism by which ZIKV sfRNA exerts its functions in vertebrate hosts and discovered a co-operation between viral noncoding RNA and a viral protein as a novel strategy employed by viruses to counteract antiviral responses.
Distinct effects of host and neighbour tree identity on arbuscular and ectomycorrhizal fungi along a tree diversity gradient
Authors: Ferlian Olga , Goldmann Kezia , Eisenhauer Nico , Tarkka Mika T. , Buscot François , Heintz-Buschart Anna 
Published: May 2021

AbstractPlant diversity and plant-related ecosystem functions have been in focus in biodiversity-ecosystem functioning studies. However, in this context, biotic interactions with mycorrhizal fungi have been understudied although they are crucial for plant-resource acquisition. We investigated the effects of tree species richness, tree mycorrhizal type on arbuscular (AMF) and ectomycorrhizal fungal (EMF) communities. We aimed to understand how dissimilarities in taxa composition and beta-diversity are related to target trees and neighbours of the same/different mycorrhizal type. We sampled a tree experiment with saplings (∼7 years old), where tree species richness (monocultures, 2-species, and 4-species mixtures) and mycorrhizal type were manipulated. AMF and EMF richness significantly increased with increasing tree species richness. AMF richness of mixture plots resembled that of the sum of the respective monocultures, whereas EMF richness of mixture plots was lower compared to the sum of the respective monocultures. Specialisation scores revealed significantly more specialised AMF than EMF suggesting that, in contrast to previous studies, AMF were more specialised, whereas EMF were not. We further found that AMF communities were little driven by the surrounding trees, whereas EMF communities were. Our study revealed the drivers of mycorrhizal fungal communities and further highlights the distinct strategies of AMF and EMF.
Survival analysis of pathway activity as a prognostic determinant in breast cancer
Authors: Jeuken Gustavo S. , Tobin Nicholas P. , Käll Lukas 
Published: May 2021

AbstractMost activities in a cell are dependent on sets of biomolecules, often referred to as pathways. Pathways are useful to study as their activities are frequently more directly related to the behavior of the cell than their components. Traditional pathway analysis gives significance to differences in the pathway components’ concentrations between sample groups. Here we instead advocate a singular value decomposition-based method for estimating individual samples’ pathway activities that allow us to investigate more advanced statistical models. Specifically, we investigate the pathway activities’ association with patients’ survival time based on the transcription profiles of the METABRIC dataset. Our implementation shows that pathway activities are better prognostic markers for survival time in METABRIC than the individual transcripts. We also demonstrate that we can regress out the effect of individual pathways on other pathways, which allows us to estimate the other pathways’ residual pathway activity on survival.
Phylogenomic analysis of the genus Pseudomonas and reclassification of P. humi, P. zeshuii, P. psychrotolerans, P. nitritireducens, P. pharmacofabricae and P. panacis are later heterotypic synonym of P. citronellolis Lang 2007, P. luteola, P. oryzihabitans, P. nitroreducens Lang 2007, P. fluvialis and P. marginalis (Brown 1918) Stevens 1925 (Approved Lists 1980), respectively
Authors: Archana Kujur Ritu Rani , Deb Sushanta , Das Subrata K 
Published: May 2021

ABSTRACTThe present study described the comparative genomic analysis of the validly named species of the genus Pseudomonas to define the taxonomic assignment. Genomic information for 208 type strains was available in the NCBI genome database at the time of conducting this analysis. The ANI, AAI and in silico DNA DNA hybridization (isDDH) data were higher than the threshold values for the twelve strains with their closely related type species. Whole genome comparisons shared 97 - 99 % average nucleotide identity, 97.85 to 99.19 % average amino acid identity and 72.80 to 90.40 % digital DNA DNA hybridization values. Further, the phylogenomic analysis based on the core genome confirmed that P. humi CCA1 and P. citronellolis LMG 18378, P. zeshuii KACC 15471 and P. luteola NBRC 103146, P. oryzihabitans DSM 6835 and P. psychrotolerans DSM 15758, P. nitroreducens DSM 14399 and P. nitritireducens WZBFD3-5A2, P. fluvialis CCM 8778 and P. pharmacofabricae ZYSR67-Z, P. panacis DSM 18529 and P. marginalis DSM 13124 formed a monophyletic clade. Thus, we proposed six type species viz., P. humi CCA1, P. zeshuii KACC 15471, P. psychrotolerans DSM 15758, P. nitritireducens WZBFD3 5A2, P. pharmacofabricae ZYSR67 Z and P. panacis DSM 18529 are the later heterotypic synonym of P. citronellolis Lang 2007, P. luteola, P. oryzihabitans, P. nitroreducens Lang 2007, P. fluvialis and P. marginalis (Brown 1918) Stevens 1925 (Approved Lists 1980), respectively considering the priority date of publication.
Detection of Locomotion Deficit in a Post-Traumatic Syringomyelia Rat Model Using Automated Gait Analysis Technique
Authors: Pukale Dipak D. , Farrag Mahmoud , Leipzig Nic D. 
Published: May 2021

AbstractSyringomyelia (SM) is a spinal cord disorder in which a cyst (syrinx) filled with fluid forms in the spinal cord post-injury/disease, in patients syrinx symptoms include loss of pain and temperature sensation or locomotion deficit. Currently, there are no small animal models and connected tools to help study the functional impacts of SM. The objective of this study was to determine the detectability of subtle locomotion deficits due to syrinx formation/expansion in post-traumatic syringomyelia (PTSM) rat model using the recently reported method of Gait Analysis Instrumentation, and Technology Optimized for Rodents (GAITOR) with Automated Gait Analysis Through Hues and Areas (AGATHA) technique. First videos of the rats were collected while walking in an arena (using GAITOR) followed by extracting meaningful locomotion information from collected videos (using AGATHA protocol. PTSM injured rats demonstrated detectable locomotion deficits in terms of duty factor imbalance, paw placement accuracy, step contact width, stride length, and phase dispersion parameters compared to uninjured rats due to SM. We concluded that this technique could detect mild and subtle locomotion deficits associated with PTSM injury, which also in future work could be used further to monitor locomotion responses after different treatment strategies for SM.
Buffered EGFR signaling regulated by spitz to argos expression ratio is critical for patterning the Drosophila eye
Authors: Pasnuri Nikhita , Jaiswal Manish , Ray Krishanu , Mazumder Aprotim 
Published: May 2021

AbstractThe Epidermal Growth Factor Receptor (EGFR) signaling pathway plays a critical role in regulating tissue patterning. Drosophila EGFR (DER) signaling achieves specificity through multiple ligands and feedback loops to finetune signaling spatiotemporally. The principal Drosophila EGF, cleaved Spitz, and the negative feedback molecule, Argos are diffusible and can act both in a cell autonomous and non-autonomous manner. The relative expression dose of Spitz and Argos early in development has been shown to be critical in patterning the Drosophila eye, but the exact identity of the cells expressing these genes in the larval eyedisc has been elusive. Using single molecule RNA Fluorescence in situ Hybridization (smFISH), we reveal an intriguing differential expression of spitz and argos in the Drosophila third instar eye imaginal disc indicative of directional DER signaling. By genetically tuning DER signaling, we show that rather than absolute levels of expression, the ratio of expression to be critical for determining the adult eye phenotype. Proper ommatidial patterning is robust to thresholds around a tightly maintained wildtype ratio, and breaks down beyond. This provides a powerful instance of developmental buffering.
Aggregation state of Mycobacterium tuberculosis impacts host immunity and augments pulmonary disease pathology
Authors: Kolloli Afsal , Kumar Ranjeet , Singh Pooja , Narang Anshika , Kaplan Gilla , Sigal Alex , Subbian Selvakumar 
Published: May 2021

ABSTRACTPhagocytosis of Mycobacterium tuberculosis (Mtb) aggregates, rather than similar numbers of single bacilli, induces host macrophage death and favors bacterial growth. Here, we examined whether aggregation contributes to enhanced Mtb pathogenicity in vivo in rabbit lungs. Rabbits were exposed to infectious aerosols containing mainly Mtb-aggregates (Mtb-AG) or Mtb-single cells (Mtb-SC). The lung bacterial load, histology, and immune cell composition were investigated over time. Genome-wide transcriptome analysis, cellular and tissue-level assays, and immunofluorescent imaging were performed on lung tissue to define and compare differential immune activation and pathogenesis between Mtb-AG and Mtb-SC infection.Lung bacillary loads, disease scores, lesion size, and structure were significantly higher in Mtb-AG than in Mtb-SC infected animals. A differential immune cell distribution and activation were noted in the lungs and spleen of the two groups of infected animals. Mtb-AG infected animals also showed early induction of inflammatory network genes associated with necrosis and reduced host cell viability. Consistently, larger lung granulomas with clumped Mtb, extensive necrotic foci, and elevated matrix metalloproteases expression were observed in Mtb-AG infected rabbits. Our findings suggest that bacillary aggregation increases Mtb fitness for improved growth and accelerated lung inflammation and cell death, thereby exacerbating disease pathology in the lungs.