bluuebunny/crossref_metadata_2025_split huggingface dataset:
Virus epidemics, plant-controlled population bottlenecks and the durability of plant resistance
Authors: Rousseau Elsa , Bonneault Mélanie , Fabre Frédéric , Moury Benoît , Mailleret Ludovic , Grognard Frédéric 
Published: May 2019

Plant qualitative resistances to viruses are natural exhaustible resources that can be impaired by the emergence of resistance-breaking (RB) virus variants. Mathematical modelling can help determine optimal strategies for resistance durability by a rational deployment of resistance in agroecosystems. Here, we propose an innovative approach, built up from our previous empirical studies, based on plant cultivars combining qualitative resistance with quantitative resistance narrowing population bottlenecks exerted on viruses during host-to-host transmission and/or within-host infection. Narrow bottlenecks are expected to slow down virus adaptation to plant qualitative resistance. To study the effect of bottleneck size on yield, we developed a stochastic epidemic model with mixtures of susceptible and resistant plants, relying on continuous-time Markov chain processes. Overall, narrow bottlenecks are beneficial when the fitness cost of RB virus variants in susceptible plants is intermediate. In such cases, they could provide up to 95 additional percentage points of yield compared with deploying a qualitative resistance alone. As we have shown in previous works that virus population bottlenecks are at least partly heritable plant traits, our results suggest that breeding and deploying plant varieties exposing virus populations to narrowed bottlenecks will increase yield and delay the emergence of RB variants.
This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.
Quantifying the consequences of measles-induced immune modulation for whooping cough epidemiology
Authors: Noori Navideh , Rohani Pejman 
Published: May 2019

Measles, an acute viral disease, continues to be an important cause of childhood mortality worldwide. Infection with the measles virus is thought to be associated with a transient but profound period of immune suppression. Recently, it has been claimed that measles-induced immune manipulation lasts for about 30 months and results in increased susceptibility to other co-circulating infectious diseases and more severe disease outcomes upon infection. We tested this hypothesis using model-based inference applied to parallel historical records of measles and whooping cough mortality and morbidity. Specifically, we used maximum likelihood to fit a mechanistic transmission model to incidence data from three different eras, spanning mortality records from 1904 to 1912 and 1922 to 1932 and morbidity records from 1946 to 1956. Our aim was to quantify the timing, severity and pathogenesis impacts of measles-induced immune modulation and their consequences for whooping cough epidemiology across a temporal gradient of measles transmission. We identified an increase in susceptibility to whooping cough following recent measles infection by approximately 85-, 10- and 36-fold for the three eras, respectively, although the duration of this effect was variable. Overall, while the immune impacts of measles may be strong and clearly evident at the individual level, their epidemiological signature in these data appears both modest and inconsistent.This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.
Detection, forecasting and control of infectious disease epidemics: modelling outbreaks in humans, animals and plants
Authors: Thompson Robin N. , Brooks-Pollock Ellen 
Published: May 2019

The 1918 influenza pandemic is one of the most devastating infectious disease epidemics on record, having caused approximately 50 million deaths worldwide. Control measures, including prohibiting non-essential gatherings as well as closing cinemas and music halls, were applied with varying success and limited knowledge of transmission dynamics. One hundred years later, following developments in the field of mathematical epidemiology, models are increasingly used to guide decision-making and devise appropriate interventions that mitigate the impacts of epidemics. Epidemiological models have been used as decision-making tools during outbreaks in human, animal and plant populations. However, as the subject has developed, human, animal and plant disease modelling have diverged. Approaches have been developed independently for pathogens of each host type, often despite similarities between the models used in these complementary fields. With the increased importance of a One Health approach that unifies human, animal and plant health, we argue that more inter-disciplinary collaboration would enhance each of the related disciplines. This pair of theme issues presents research articles written by human, animal and plant disease modellers. In this introductory article, we compare the questions pertinent to, and approaches used by, epidemiological modellers of human, animal and plant pathogens, and summarize the articles in these theme issues. We encourage future collaboration that transcends disciplinary boundaries and links the closely related areas of human, animal and plant disease epidemic modelling.
This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.
TractEM: Fast Protocols for Whole Brain Deterministic Tractography-Based White Matter Atlas
Authors: Bayrak Roza G. , Wang Xuan , Schilling Kurt G. , Greer Jasmine M. , Hansen Colin B. , Blaber Justin A. , Williams Owen , Beason-Held Lori L. , Resnick Susan M. , Rogers Baxter P. , Landman Bennett A. 
Published: May 2019

AbstractReproducible identification of white matter tracts across subjects is essential for the study of structural connectivity of the human brain. The key challenges are anatomical differences between subjects and human rater subjectivity in labeling. Labeling white matter regions of interest presents many challenges due to the need to integrate both local and global information. Clearly communicating the human/manual processes to capture this information is cumbersome, yet essential to lay a solid foundation for comprehensive atlases. The state-of-the-art for white matter atlas is the single population-averaged Johns Hopkins Eve atlas. A critical bottleneck with the Eve atlas framework is that manual labeling time is extensive and peripheral white matter regions are conservatively labeled. In this work, we developed protocols that will facilitate manual virtual dissection of white matter pathways, with the goals to be anatomically accurate, intuitive, reproducible, and act as an initial stage to build an amenable knowledge base of neuroanatomical regions. We analyzed reproducibility of the fiber bundles and variability of human raters using DICE correlation coefficient, intraclass correlation coefficient, and root mean squared error. The protocols at their initial stage have shown promising results on both typical 3T research acquisition Baltimore Longitudinal Study of Aging and high-acquisition quality Human Connectome Project datasets. The TractEM manual labeling protocols allow for reconstruction of reproducible subject-specific fiber bundles across the brain. The protocols and sample results have been made available in open source to improve generalizability and reliability in collaboration.
Estimating Rates of Progression and Predicting Future Visual Fields in Glaucoma Using a Deep Variational Autoencoder
Authors: Berchuck Samuel I. , Mukherjee Sayan , Medeiros Felipe A. 
Published: May 2019

ABSTRACTPurposeTo develop a novel deep learning algorithm to improve estimation of rates of progression and prediction of future patterns of visual field loss in glaucoma.DesignProspective observational cohort.MethodsA variational auto-encoder (VAE) was trained to learn a low-dimensional feature representation of standard automated perimetry (SAP) visual fields using 29,161 fields from 3,832 patients. The VAE was trained on a 90% sample of the data, with randomization at the patient level. Using the remaining 10%, rates of progression and predictions were generated, with comparisons to SAP mean deviation (MD) rates and point-wise (PW) regression predictions, respectively. From the VAE, rates were calculated using the average of slopes across latent features from ordinary least squares (OLS) regression and trajectories of the features were used to generate predictions.ResultsThe longitudinal rate of change through the VAE latent space (e.g., with eight dimensions) detected a significantly higher proportion of progression than MD at two (19% vs. 6%) and four (40% vs 14%) years from baseline. Early on, VAE improved prediction over PW, with significantly smaller mean absolute error in predicting the 4th, 6th and 8th visits from the first three (e.g., visit eight: VAE8: 4.06 dB vs. PW: 6.06 dB; P<0.001).ConclusionA deep VAE can be used for assessing both rates and trajectories of progression in glaucoma, with the additional benefit of being a generative technique capable of predicting future patterns of visual field damage in the disease.
Effects of Serotonin and Dopamine Depletion on Neural Prediction Computations during Social Learning
Authors: Frey Anna-Lena , McCabe Ciara 
Published: May 2019

AbstractWe recently found that individuals with high depression scores demonstrate impaired learning from social outcomes. Given that depression has been linked to altered serotonin (5-HT) and dopamine (DA) functioning, the current study aimed to elucidate the role of these neurotransmitters in social learning with the use of dietary precursor depletion. In a double-blind design, 70 healthy volunteers were randomly allocated to the 5-HT depletion (N=24), DA depletion (N = 24), or placebo (N = 22) group. Participants performed a social learning task during fMRI scanning, as part of which they learned associations between name cues and rewarding (happy faces) or aversive (fearful faces) social outcomes. Behaviourally, 5-HT depleted subjects demonstrated impaired social reward learning compared to placebo controls, with a marginal effect in the same direction in the DA depletion group. On the neural level, computational modelling-based fMRI analyses revealed that 5-HT depletion altered social reward prediction signals in the insula, temporal lobe, and prefrontal cortex. DA depletion affected social reward prediction encoding only in the prefrontal cortex. These results indicate that 5-HT depletion impairs learning from social rewards, on both the behavioural and the neural level, while DA depletion has a less extensive effect. Interestingly, the behavioural and neural responses observed after 5-HT depletion in the current study closely resemble our previous findings in individuals with high depression scores. It may thus be the case that decreased 5-HT levels contribute to social learning deficits in depression.
The categorical neural organization of speech aids its perception in noise
Authors: Bidelman Gavin M. , Bush Lauren C. , Boudreaux Alex M. 
Published: May 2019

ABSTRACTWe investigated whether the categorical perception (CP) of speech might also provide a mechanism that aids its perception in noise. We varied signal-to-noise ratio (SNR) [clear, 0 dB, -5 dB] while listeners classified an acoustic-phonetic continuum (/u/ to /a/). Noise-related changes in behavioral categorization were only observed at the lowest SNR. Event-related brain potentials (ERPs) differentiated phonetic vs. non-phonetic (category ambiguous) speech by the P2 wave (∼180-320 ms). Paralleling behavior, neural responses to speech with clear phonetic status (i.e., continuum endpoints) were largely invariant to noise, whereas responses to ambiguous tokens declined with decreasing SNR. Results demonstrate that phonetic speech representations are more resistant to degradation than corresponding acoustic representations. Findings suggest the mere process of binning speech sounds into categories provides a robust mechanism to aid perception at the “cocktail party” by fortifying abstract categories from the acoustic signal and making the speech code more resistant to external interferences.
Antioxidants maintain Butyrate production by Human GutClostridiain the presence of Oxygen
Authors: Million Matthieu , Armstrong Nicholas , Khelaifia Saber , Guilhot Elodie , Richez Magali , Lagier Jean-Christophe , Dubourg Gregory , Chabriere Eric , Raoult Didier 
Published: May 2019

ABSTRACTBackgroundOxygen diffused from the human gut mucosa and shape the microbiota with a radial gradient of microbes according to their oxygen tolerance, while microbial and chemical oxygen consumption maintains the lumen in a deeply anaerobic state. Uncontrolled oxidative stress and hyperoxygenation have been reported as a pathogenic mechanism inSalmonellaorCitrobacter rodentiuminfection, in patients with HIV and in severe acute malnutrition. We recently found that antioxidants allow strict anaerobes, including methanogenic archaea, to thrive in an oxidative environment (aerobic). Here, we tested the metabolomics switching of the 3 most odorous anaerobic microbes isolated from human gut when grown in aerobiosis with antioxidants.MethodsThree human gut Clostridia,Clostridium sporogenes, Clostridium lituseburenseandClostridium subterminale, isolated by culturomics, were grown in anaerobiosis or in aerobiosis with antioxidants. Gaz and liquid chromatography-Mass spectrometry (GC/MS and LC/MS) were used for metabolomics analysis.ResultsAn unexpected global dichotomic metabolomic switching from thiols, alcohols and short-chain fatty acid esters to a specific aerobic metabolic repertoire with the production of alkanes, cycloheptatriene and, paradoxically, increased butyrate production, was observed. Analysis of polar metabolites confirmed the discovery of an unexplored aerobic metabolic repertoire, including the production of specific dipeptides and several lysophospholipids, thus unraveling unsuspected human gut microbiome capacities.ConclusionsAntioxidants unraveled an unexplored aerobic metabolic repertoire of human gutClostridia. The increased production of butyrate suggests that antioxidants contribute to the maintenance and the active resilience of the human gut microbiome against oxidative aggression, as duringSalmonellainfection.
Microbial dysbiosis and its implications for disease in a genetically depauperate species
Authors: DeCandia Alexandra L. , King Julie L. , vonHoldt Bridgett M. 
Published: May 2019

ABSTRACTTHE host-associated microbiome is increasingly recognized as a critical player in health and immunity. When commensal microbial communities are disrupted, dysbiosis can contribute to disease pathogenesis and severity. Santa Catalina Island foxes (Urocyon littoralis catalinae) present an ideal case study for examining dysbiosis in wildlife due to their depauperate genomic structure and extremely high prevalence of ear canal tumors. Although the precise cause is yet unknown, infection with ear mites (Otodectes cynotis) has been linked to chronic inflammation, which is associated with abnormal cell growth and tumor development. Given the paucity of genomic variation in these foxes, other dimensions of molecular diversity, such as commensal microbes, may be critical to host response and adaptation. We therefore characterized the host-associated microbiome across six body sites of Santa Catalina Island foxes, and performed differential abundance testing between healthy and mite-infected ear canals. We found that mite infection was significantly associated with reduced microbial diversity and evenness, with the opportunistic pathogenStaphylococcus pseudintermediusdominating the ear canal community. These results suggest that secondary bacterial infection may contribute to the sustained inflammation associated with tumor development. Uncovering high abundance ofS. pseudintermediusprovides critical insight into the pathogenesis of this complex system, as the emergence of antibiotic resistant strains remains a concern of the medical, veterinary, and conservation communities. Through use of culture-independent sequencing techniques, this study contributes to the broader effort of applying a more inclusive understanding of molecular diversity to questions within wildlife disease ecology.
Single-cell information analysis reveals small intra- and large intercellular variations increase cellular information capacity
Authors: Wada Takumi , Wataya Mitsutaka , Fujii Masashi , Hironaka Ken-ichi , Eto Miki , Uda Shinsuke , Hoshino Daisuke , Kunida Katsuyuki , Inoue Haruki , Kubota Hiroyuki , Hamaguchi Hiroki , Furuichi Yasuro , Manabe Yasuko , Fujii Nobuharu L. , Kuroda Shinya 
Published: May 2019

AbstractCells transmit information about extracellular stimulation through signaling pathways to control cellular function. A signaling pathway can be regarded as a communication channel. In the analysis of channels of cell populations, intercellular variation is considered noise. However, intercellular variation enables individual cells to encode different information. Therefore, at the single-cell level, each cell can be regarded as an independent channel. Thus, we propose that responses of cells of the same type in tissues, such as the fibers in a skeletal muscle, should be regarded as a multiple-cell channel composed of single-cell channels, in which intercellular variation contains information. Here, we applied electrical pulses to individual myotubes from cultured C2C12 cells or dissociated skeletal muscle fibers and measured Ca2+ responses or contraction, respectively, to estimate information capacity in a biological system. For each muscle cell system, we found that a single-cell channel transmitted more information than did a cell-population channel, indicating that the cellular response is consistent with each cell (low intracellular variation) but different among individual cells (high intercellular variation). As cell number and thus the number of single-cell channels increased, a multiple-cell channel transmitted more information by incorporating the differences among individual cells. Thus, a tissue with small intracellular and large intercellular variations has the capacity to distinguish differences in stimulation intensity to precisely control physiological function.One Sentence SummarySmall intracellular and large intercellular variations increase information transmission for precise control of tissue function.
Associations of ‘Relative corticosterone deficiency’ with genetic variation in CYP17A1 and metabolic syndrome features
Authors: Mackenzie Scott D , Crawford Andrew A , Ackermann Daniel , Schraut Katharina E , Hayward Caroline , Bolton Jennifer L , Saunders Christopher , Al-Dujaili Emad , Dick Bernhard , Escher Geneviève , Vogt Bruno , Pruijm Menno , Ponte Belen , Wilson James F , Strachan Mark W J , Price Jackie F , Phillips David I W , MacKenzie Scott M , Davies Eleanor , Reynolds Rebecca M , Walker Brian R 
Published: May 2019

ABSTRACTContext and objectiveCommon genetic variants in CYP17A1 associate with higher blood pressure, putatively from impaired 17α-hydroxylase activity and mineralocorticoid excess. However, the same variants protect against obesity and insulin resistance. We tested whether CYP17A1 variants that enhance 17α-hydroxylase activity cause ‘relative corticosterone deficiency’. Since corticosterone is thought to contribute disproportionately to negative feedback in the hypothalamic-pituitary-adrenal axis, we also tested whether lower corticosterone associates with higher cortisol and hence with metabolic syndrome.DesignCross-sectional studies within the population-based Orkney Complex Disease Study (ORCADES; n=2018), VIKING Health Study Shetland (VIKING; n=2098), East Hertfordshire study (EHERTS; n=279), Edinburgh Type 2 Diabetes Study (ET2DS; n=903), and the Swiss Kidney Project on Genes in Hypertension (SKIPOGH; n=888).Outcome measuresCortisol and corticosterone in morning plasma samples in ORCADES, VIKING and ET2DS, and in EHERTS in plasma following overnight dexamethasone suppression (0.25mg) and 30 mins after ACTH1-24 (1µg); cortisol and corticosterone metabolites in day and night urine samples in SKIPOGH. Features of the metabolic syndrome including body mass index, systolic blood pressure, lipid profile, fasting glucose, fasting insulin and HOMA-IR.ResultsIn ORCADES, ET2DS and SKIPOGH, CYP17A1 variants were associated with corticosterone:cortisol ratio. In ORCADES, VIKING and ET2DS there were consistent associations of morning plasma cortisol and corticosterone with BMI, blood pressure, lipid profile, fasting glucose and HOMA-IR. In EHERTS, however, after dexamethasone suppression and ACTH1-24 stimulation, impaired glucose tolerance and insulin sensitivity were associated with higher cortisol but lower corticosterone. Similarly, in SKIPOGH, low corticosterone:cortisol metabolite ratios were associated with high BMI and dyslipidemia.Conclusions‘Relative corticosterone deficiency’, due to a primary alteration in adrenal steroidogenesis favouring cortisol over corticosterone, may mediate the associations of genetic variation in CYP17A1 with metabolic syndrome. However, additional determinants of variation in plasma corticosterone are likely to explain its generally positive associations with features of metabolic syndrome.
Reduced Telomerase Interaction with Telomeres Alters Meiotic Chromosome Motion and Gamete Viability
Authors: Smith Dana L. , Oke Ashwini , Pollard Michael , Anderson Carol M. , Zhuge Tangna , Yam Phoebe , Gromova Tatiana , Conant Kaylynn , Chu Daniel B. , Patel Neem J. , Gonzalez Fernanda , Stoddard Caitlin , Burgess Sean , Hochwagen Andreas , Marshall Wallace F. , Blackburn Elizabeth , Fung Jennifer C. 
Published: May 2019

AbstractWe report a role for telomerase, beyond its known function of telomeric DNA end extension, in maintaining normal chromosome dynamics during meiosis inSaccharomyces cerevisiae.When telomerase at telomeres was reduced by various genetic means, increased frequencies of crossover and noncrossover recombination events occurred. To investigate the mechanism of this increased meiotic recombination, we examined the kinetics of meiosis events, and tracked the movement of chromosomes in live cells during meiotic prophase. Cytoskeletal forces acting on telomeres during meiosis have been shown to promote active chromosome motion needed to pair homologous chromosomes. Here we show that changes in telomerase interaction with telomeres using a tlc1-11 mutant result in altered meiotic motion. Specifically, reduction in telomerase at telomeres leads to a decreased frequency of high velocity chromosome pulls. In the tlc1-11 mutant, we see earlier synapsis and increased genome-wide recombination for the majority of the cells and lower gamete viability. Notably, homologous pairing is not delayed unlike other telomere binding mutants. Although synapsis initiates earlier, the overall timing of synapsis remains the same, except for a subset of cells that do not exit meiosis I. Together, these results suggest that the strong pulling component of the active chromosome motion promotes homolog pairing fidelity, likely by pulling apart improperly associated regions. Our combined observations are consistent with a model in which telomerase-mediated telomeric anchoring to the nuclear envelope helps engage and properly transmit cytoskeletal forces to chromosomes. Thus, telomerase contributes to efficient chromosome movements leading to normal gamete viability.