bluuebunny/crossref_metadata_2025_split huggingface dataset:
Necrotizing enterocolitis-induced systemic immune suppression in neonatal preterm pigs
Authors: Ren Shuqiang , Pan Xiaoyu , Hui Yan , Kot Witold , Gao Fei , Sangild Per T. , Nguyen Duc Ninh 
Published: September 2020

AbstractObjectivesPreterm infants are at high risks of sepsis and necrotising enterocolitis (NEC). Some develop sepsis shortly after suspected or confirmed NEC, implying that NEC may predispose to sepsis but the underlying mechanisms are unknown. Using NEC-sensitive preterm pigs as models, we investigated the immune status in animals with and without NEC.MethodsPreterm pigs (n=113, caesarean delivered at day 106) were reared until day 5 or 9. Blood was analyzed for T cell subsets, neutrophil phagocytosis, trans criptomics and immune responses to LPS challenge. Gut tissues were used for histology and cytokine analyses. Pigs with/without macroscopic NEC lesions were scored as healthy, mild or severe NEC.ResultsOverall NEC incidence was similar on days 5 and 9 (61-62%) with less severe lesions on day 9, implying gradual mucosal repair following the early phase of NEC on day 5. Pigs with NEC, especially severe NEC, showed decreased goblet cell density and increased MPO+and CD3+cell density in the distal intestine or colon. Circulating parameters were minimally affected by NEC on day 5, but widely altered on day 9 in pigs with NEC, especially severe NEC, to the direction of immune suppression. These included elevated Treg frequency, impaired neutrophil phagocytosis, diminished LPS-induced cytokine secretions and immune gene responses, and consistently low expressions of genes related to innate immune signalling and Th1 polarization.ConclusionWe shows evidence for NEC-induced systemic immune suppression, even with mild and sub-clinical NEC lesions, thereby suggesting mechanisms for increased secondary infections in infants with previous NEC diagnosis.
SingleChannelNet: A Model for Automatic Sleep Stage Classification with Raw Single-Channel EEG
Authors: Zhou Dongdong , Hu Guoqiang , Zhang Jiacheng , Wang Jian , Yan Rui , Li Fan , Xu Qi , Kettunen Lauri , Chang Zheng , Cong Fengyu 
Published: September 2020

AbstractIn diagnosing sleep disorders, sleep stage classification is a very essential yet time-consuming process. Most of the existing state-of-the-art approaches rely on hand-crafted features and multi-modality polysomnography (PSG) data, where prior knowledge is compulsory and high computation cost can be expected. Besides, few studies are able to obtain high accuracy sleep staging using raw single-channel electroencephalogram (EEG). To overcome these shortcomings, this paper proposes an end-to-end framework with a deep neural network, namely SingleChannelNet, for automatic sleep stage classification based on raw single-channel EEG. The proposed model utilizes a 90s epoch as the textual input and employs two multi-convolution blocks and several max-average pooling layers to learn different scales of feature representations. To demonstrate the efficiency of the proposed model, we evaluate our model using different raw single-channel EEGs (C4/A1 and Fpz-Cz) on two different datasets (CC-SHS and Sleep-EDF datasets). Experimental results show that the proposed architecture can achieve better over-all accuracy and Cohen’s kappa (CCSHS: 90.2%-86.5%, Sleep-EDF: 86.1%-80.5%) compared with state-of-the-art approaches. Additionally, the proposed model can learn features automatically for sleep stage classification using different single-channel EEGs with distinct sampling rates from different datasets without using any hand-engineered features.
Neonicotinoids stimulate H2-limited methane emission inPeriplaneta americanathrough the regulation of gut bacterium community
Authors: Bao Haibo , Gao Haoli , Zhang Jianhua , Lu Haiyan , Yu Na , Shao Xusheng , Zhang Yixi , Jin Wei , Li Shuqing , Xu Xiaoyong , Tian Jiahua , Xu Zhiping , Li Zhong , Liu Zewen 
Published: September 2020

AbstractMethane emitted by insects is considered to be an important source of atmospheric methane. Here we report the stimulation of methane emission inPeriplaneta americana, an insect species with abundant methanogens, by neonicotinoids, insecticides widely used to control insect pests. The application of cycloxaprid (CYC) and imidacloprid (IMI) caused foregut expansion inP. americana, and increased the methane production and emission. Antibiotics could mostly eliminate the stimulatory effects. InP. americanagut, hydrogen levels increased and pH values decreased, which could be significantly explained by the gut bacterium community change. The proportion of several bacterium genera increased in guts following CYC treatment, and four genera from five with increased proportions could generate hydrogen at anaerobic conditions. Hydrogen is a central intermediate in methanogenesis. Gut methanogens could use the increased hydrogen to produce more methane, especially at acidic conditions. Following neonicotinoid applications, all increased methanogens in both foregut and hindgut used hydrogen as electron donor to produce methane. Besides, the up-regulation ofmcrA, encoding the enzyme that catalyzes the final step of methanogenesis, suggested an enhanced methane production ability in present methanogens. In the termiteCoptotermes chaohuensis, another methanogen-abundant insect species, hydrogen levels in gut and methane emission significantly increased after neonicotinoid treatment, which was similar to the results inP. americana. In summary, neonicotinoids changed bacterium community inP. americanagut to generate more hydrogen, which then stimulate gut methanogens to produce and emit more methane. The finding raised a new concern over neonicotinoid applications, and might be a potential environmental risk associated with global warming.
Electron flow through NDH-1 complexes is the major driver of cyclic electron flow-dependent proton pumping in cyanobacteria
Authors: Miller Neil T. , Vaughn Michael D. , Burnap Robert L. 
Published: September 2020

AbstractCyclic electron flow (CEF) around Photosystem I is vital to balancing the photosynthetic energy budget of cyanobacteria and other photosynthetic organisms. The coupling of CEF to proton pumping has long been hypothesized to occur, providing proton motive force (PMF) for the synthesis of ATP with no net cost to [NADPH]. This is thought to occur largely through the activity of NDH-1 complexes, of which cyanobacteria have four with different activities. While a much work has been done to understand the steady-state PMF in both the light and dark, and fluorescent probes have been developed to observe these fluxesin vivo, little has been done to understand the kinetics of these fluxes, particularly with regard to NDH-1 complexes. To monitor the kinetics of proton pumping inSynechocystissp. PCC 6803, the pH sensitive dye Acridine Orange was used alongside a suite of inhibitors in order to observe light-dependent proton pumping. The assay was demonstrated to measure photosynthetically driven proton pumping and used to measure the rates of proton pumping unimpeded by dark ΔpH. Here, the cyanobacterial NDH-1 complexes are shown to pump a sizable portion of proton flux when CEF-driven and LEF-driven proton pumping rates are observed and compared in mutants lacking some or all NDH-1 complexes. It is also demonstrated that PSII and LEF are responsible for the bulk of light induced proton pumping, though CEF and NDH-1 are capable of generating ∼40% of the proton pumping rate when LEF is inactivated.Highlights statementNDH-1 is essential for proton pumping during cyclic photosynthetic electron flow in cyanobacteria
Virulence evolution of multiple infections with vertically and horizontally transmitted fungal species in a natural plant system
Authors: Fang Kai , Zhou Jie , Chen Lin , Li Yu-Xuan , Yang Ai-Ling , Dong Xing-Fan , Zhang Han-Bo 
Published: September 2020

AbstractThe virulence evolution of multiple infections of parasites from the same species has been modelled widely in evolution theory, and the trajectories of evolution are relevant to parasite transmission mode, as well as to parasite and host population dynamics. However, experimental studies on this topic remain scarce, particularly regarding multiple infections by different parasite species. In this study, we employed the invasive plantAgeratina adenophorato verify the predictions made by the model. We observed thatA. adenophorawas a highly susceptible host to phylogenetically diverse foliar pathogens with mixed vertical and horizontal transmission within leaf spots. The pathogen community structure at the leaf spot level was determined by transmission mode. Over time, the pathogen community decreased in diversity; meanwhile, the vertically transmitted pathogens exhibited decreased virulence to the hostA. adenophora, but the horizontally transmitted pathogens exhibited increased virulence to the host. Our results demonstrate that the predictions of classical models are still valid in a complex environment. Moreover, we propose that it is very important to determine whether the primary foliar pathogen of a given plant host is relevant to seedborne fungi, as this characteristic is an important factor in understanding pathogen-host interactions.
Genetic Architecture of 11 Major Psychiatric Disorders at Biobehavioral, Functional Genomic, and Molecular Genetic Levels of Analysis
Authors: Grotzinger Andrew D. , Mallard Travis T. , Akingbuwa Wonuola A. , Ip Hill F. , Adams Mark J. , Lewis Cathryn M. , McIntosh Andrew M. , Grove Jakob , Dalsgaard Søren , Lesch Klaus-Peter , Strom Nora , Meier Sandra M. , Mattheisen Manuel , Børglum Anders D. , Mors Ole , Breen Gerome ,   iPSYCH, Tourette Syndrome and Obsessive Compulsive Disorder Working Group of the Psychiatric Genetics Consortium,   Bipolar Disorder Working Group of the Psychiatric Genetics Consortium,   Major Depressive Disorder Working Group of the Psychiatric Genetics Consortium,   Schizophrenia Working Group of the Psychiatric Genetics Consortium, Lee Phil H. , Kendler Kenneth S. , Smoller Jordan W. , Tucker-Drob Elliot M. , Nivard Michel G. 
Published: September 2020

AbstractWe systematically interrogate the joint genetic architecture of 11 major psychiatric disorders at biobehavioral, functional genomic, and molecular genetic levels of analysis. We identify four broad factors (Neurodevelopmental, Compulsive, Psychotic, and Internalizing) that underlie genetic correlations among the disorders, and test whether these factors adequately explain their genetic correlations with biobehavioral traits. We introduce Stratified Genomic Structural Equation Modelling, which we use to identify gene sets and genomic regions that disproportionately contribute to pleiotropy, including protein-truncating variant intolerant genes expressed in excitatory and GABAergic brain cells that are enriched for pleiotropy between disorders with psychotic features. Multivariate association analyses detect a total of 152 (20 novel) independent loci which act on the four factors, and identify nine loci that act heterogeneously across disorders within a factor. Despite moderate to high genetic correlations across all 11 disorders, we find very little utility of, or evidence for, a single dimension of genetic risk across psychiatric disorders.
Knowledge, Attitude and Practice towards COVID-19 among people in Bangladesh during the pandemic: a cross-sectional study
Authors: Rabbani Md. Golam , Akter Orin , Hasan Md. Zahid , Samad Nandeeta , Mahmood Shehrin Shaila , Joarder Taufique 
Published: September 2020

AbstractThe world is grappling with Covid-19, a dire public health crisis. Preventive and control measures are adopted to reduce the spread of COVID-19. It is important to know the knowledge, attitude, and practice (KAP) of people towards this pandemic to suggest appropriate coping strategies. The aim of this study was to assess the KAP of Bangladeshi people towards Covid-19 and determinants of those KAPs. We conducted a cross-sectional survey of 492 Bangladeshi people aged above 18 years from May 7 to 29, 2020 throughout the country. Simple and multiple logistic regression analyses were conducted to identify the factors associated with KAP on COVID-19. About 45% of respondents had good knowledge, 49% of respondents expressed positive attitude towards controlling of COVID-19 and 24% of respondents had favorable practice towards COVID-19. Almost three fourths of the respondents went outside home during the lockdown period. Furthermore, the study found that good knowledge and attitude were associated with better practice of COVID-19 health measures. An evidence informed and context specific risk communication and community engagement, and a social and behavior change communication strategy against COVID-19 should be developed in Bangladesh, based on the findings of this study, targeting different socio-economic groups.
Increased resting-state functional connectivity within theta and alpha frequency bands in dysphoria: Towards a novel measure of depression risk
Authors: Dell’Acqua Carola , Ghiasi Shadi , Benvenuti Simone Messerotti , Greco Alberto , Gentili Claudio , Valenza Gaetano 
Published: September 2020

AbstractBackgroundThe understanding of neurophysiological correlates underlying the risk of developing depression may have a significant impact on its early and objective identification. Research has identified abnormal resting-state electroencephalography (EEG) power and functional connectivity patterns in major depression. However, the entity of dysfunctional EEG dynamics in dysphoria is yet unknown.Methods32-channel EEG was recorded in 26 female individuals with dysphoria and in 38 age-matched, female healthy controls. EEG power spectra and alpha asymmetry in frontal and posterior channels were calculated in a 4-minute resting condition. An EEG functional connectivity analysis was conducted through phase locking values, particularly mean phase coherence.ResultsWhile individuals with dysphoria did not differ from controls in EEG spectra and asymmetry, they exhibited dysfunctional brain connectivity. Particularly, in the theta band (4-8 Hz), participants with dysphoria showed increased connectivity between right frontal and central areas and right temporal and left occipital areas. Moreover, in the alpha band (8-12 Hz), dysphoria was associated with increased connectivity between right and left prefrontal cortex and between frontal and central-occipital areas bilaterally.LimitationsAll participants belonged to the female gender and were relatively young. Mean phase coherence did not allow to compute the causal and directional relation between brain areas.ConclusionsAn increased EEG functional connectivity in the theta and alpha bands characterizes dysphoria. These patterns may be associated with the excessive self-focus and ruminative thinking that typifies depressive symptoms. EEG connectivity patterns may represent a promising measure to identify individuals with a higher risk of developing depression.
Reduced heart rate variability is associated with vulnerability to depression
Authors: Dell’Acqua Carola , Bò Elisa Dal , Benvenuti Simone Messerotti , Palomba Daniela 
Published: September 2020

AbstractBackgroundHeart rate variability (HRV) mirrors cardiac autonomic modulation, an index of well-being. Reduced HRV has been reported in depression, but few studies investigated HRV in individuals at-risk of or remitted from a full-blown depressive episode. The present study aimed at examining whether reduced HRV could be a potential indicator of vulnerability to depression.MethodsSelf-reported psychological measures and three-minute resting-state ECG were collected in two at-risk populations [group with dysphoria (n= 27), group with past depression (n= 16)] and in a control group (n= 25). Time- and frequency-domain HRV parameters were computed. Analysis of covariance was conducted to detect between-groups differences for each measure.ResultsStandard Deviation of Normal to Normal intervals (SDNN) and High Frequency (HF) power of HRV were found to be reduced both in individuals with dysphoria and in those with past depression as compared with controls. Whereas psychological measures did not significantly differ among individuals with past depression and controls, HRV was capable of discriminating between the two groups.LimitationsPast depression was assessed retrospectively with self-reported information. The inclusion of a group with depression would provide an overview about HRV during the illness course.ConclusionsThe findings suggest that reduced HRV is likely to be implicated in the risk of developing full-blown depression, rather than being a mere correlate of current depressive state. The results suggest that HRV may improve clinicians’ ability to early identify people at risk for depression who can benefit from targeted prevention by psychiatric and psychological interventions.
A statistical algorithm for outbreak detection in a multi-site setting: the case of sick leave monitoring
Authors: Duchemin Tom , Noufaily Angela , Hocine Mounia N. 
Published: September 2020

AbstractSurveillance for infectious disease outbreak or for other processes should sometimes be implemented simultaneously on multiple sites to detect local events. Sick leave can be monitored accross companies to detect issues such as local outbreaks and identify companies-related issues as local spreading of infectious diseases or bad management practice. In this context, we proposed an adaptation of the Quasi-Poisson regression-based Farrington algorithm for multi-site surveillance. The proposed algorithm consists of a Negative-Binomial mixed effect regression with a new reweighting procedure to account for past outbreaks and increase sensitivity of the model. We perform a wide range simulations to assess the performance of the model in terms of False Positive Rate and Probability of Detection. We propose an application to sick leave rate in the context of COVID-19. The proposed algorithm provides good overall performance and opens up new opportunities for multi-site data surveillance.
Aerosol transmission of COVID-19 and infection risk in indoor environments
Authors: Lelieveld J. , Helleis F. , Borrmann S. , Cheng Y. , Drewnick F. , Haug G. , Klimach T. , Sciare J. , Su H. , Pöschl U. 
Published: September 2020

AbstractThe role of aerosolized SARS-CoV-2 viruses in airborne transmission of COVID-19 is debated. The transmitting aerosol particles are generated through the breathing and vocalization by infectious subjects. Some authors state that this represents the dominant route of spreading, while others dismiss the option. Public health organizations generally categorize it as a secondary transmission pathway. Here we present a simple, easy-to-use spreadsheet algorithm to estimate the infection risk for different indoor environments, constrained by published data on human aerosol emissions, SARS-CoV-2 viral loads, infective dose and other parameters. We evaluate typical indoor settings such as an office, a classroom, a choir practice room and reception/party environments. These are examples, and the reader is invited to use the algorithm for alternative situations and assumptions. Our results suggest that aerosols from highly infective subjects can effectively transmit COVID-19 in indoor environments. This “highly infective” category represents about one fifth of the patients tested positive for SARS-CoV-2. We find that “super infective” subjects, representing the top few percent of positive-tested ones, plus an unknown fraction of less, but still highly infective, high aerosol-emitting subjects, may cause COVID-19 clusters (>10 infections), e.g. in classrooms, during choir singing and at receptions. The highly infective ones also risk causing such events at parties, for example. In general, active room ventilation and the ubiquitous wearing of face masks (i.e. by all subjects) may reduce the individual infection risk by a factor of five to ten, similar to high-volume HEPA air filtering. The most effective mitigation measure studied is the use of high-quality masks, which can drastically reduce the indoor infection risk through aerosols.
A microplanning strategy to improve door-to-door health service delivery: The case of Seasonal Malaria Chemoprevention in Sub-Saharan African villages
Authors: Ouédraogo André Lin , Zhang Julie , Tinto Halidou , Valéa Innocent , Wenger Edward A. 
Published: September 2020

AbstractBackgroundMalaria incidence has plateaued in Sub-Saharan Africa despite Seasonal Malaria Chemoprevention’s introduction. Community health workers use a door-to-door delivery strategy to treat children with SMC drugs, but for SMC to be as effective as in clinical trials, coverage must be high over successive seasons.MethodsWe developed and used a microplanning model that ‘utilizes raster to estimate population size, generates optimal households visit itinerary, and quantifies SMC coverage based on CHWs’ time investment for treatment and walking. CHWs’ performance under current SMC deployment mode was assessed using CHWs’ tracking data and compared to microplanning in villages with varying demographics and geographies.ResultsEstimates showed that microplanning significantly reduces CHWs’ walking distance by 25%, increases the number of visited households by 36% (p < 0.001) and increases SMC coverage by 21% from 37.3% under current SMC deployment mode up to 58.3% under microplanning (p < 0.001). Optimal visit itinerary alone increased SMC coverage up to 100% in small villages whereas in larger or hard-to-reach villages, filling the gap additionally needed an optimization of the CHW ratio.ConclusionWe estimate that for a pair of CHWs, the daily optimal number of visited children (assuming 8.5mn of treatment duration per child) and walking distance should not exceed 45 and 5km respectively. Our work contributes to extend SMC coverage by 21-63% and may have broader applicability for other community health programs.
Risk of adverse COVID-19 outcomes for people living with HIV: a rapid review and meta-analysis
Authors: Mellor Maya M. , Bast Anne C. , Jones Nicholas R. , Roberts Nia W. , Ordóñez-Mena José M. , Reith Alastair J.M. , Butler Christopher C. , Matthews Philippa C. , Dorward Jienchi 
Published: September 2020

AbstractObjectiveTo assess whether people living with HIV (PLWH) are at increased risk of COVID-19 mortality or adverse outcomes, and whether antiretroviral therapy (ART) influences this risk.DesignRapid review with meta-analysis and narrative synthesis.MethodsWe searched databases including Embase, Medline, medRxiv, and Google Scholar up to 26th August 2020 for studies describing COVID-19 outcomes in PLWH and conducted a meta-analysis of higher quality studies.ResultsWe identified 1,908 studies and included 19 in the review. In a meta-analysis of five studies, PLWH had a higher risk of COVID-19 mortality (hazard ratio (HR) 1.93, 95% Confidence Interval (CI): 1.59-2.34) compared to people without HIV. Risk of death remained elevated for PLWH in a subgroup analysis of hospitalised cohorts (HR 1.54, 95% CI: 1.05-2.24) and studies of PLWH across all settings (HR 2.08, 95%CI: 1.69-2.56). Eight other studies assessed the association between HIV and COVID-19 outcomes, but provided inconclusive, lower-quality evidence due to potential confounding and selection bias.There were insufficient data on the effect of CD4+ T cell count and HIV viral load on COVID-19 outcomes. Eleven studies reported COVID-19 outcomes by ART-regimen. In the two largest studies, tenofovir-disoproxil-fumarate (TDF)-based regimens were associated with a lower risk of adverse COVID-19 outcomes, although these analyses are susceptible to confounding by comorbidities.ConclusionEvidence is emerging that suggests a moderately increased risk of COVID-19 mortality amongst PLWH. Further investigation into the relationship between COVID-19 outcomes and CD4+ T cell count, HIV viral load, ART and the use of TDF is warranted.