bluuebunny/crossref_metadata_2025_split huggingface dataset:
Perfect counterfactuals for epidemic simulations
Authors: Kaminsky Joshua , Keegan Lindsay T. , Metcalf C. Jessica E. , Lessler Justin 
Published: May 2019

Simulation studies are often used to predict the expected impact of control measures in infectious disease outbreaks. Typically, two independent sets of simulations are conducted, one with the intervention, and one without, and epidemic sizes (or some related metric) are compared to estimate the effect of the intervention. Since it is possible that controlled epidemics are larger than uncontrolled ones if there is substantial stochastic variation between epidemics, uncertainty intervals from this approach can include a negative effect even for an effective intervention. To more precisely estimate the number of cases an intervention will prevent within a single epidemic, here we develop a ‘single-world’ approach to matching simulations of controlled epidemics to their exact uncontrolled counterfactual. Our method borrows concepts from percolation approaches, prunes out possible epidemic histories and creates potential epidemic graphs (i.e. a mathematical representation of all consistent epidemics) that can be ‘realized’ to create perfectly matched controlled and uncontrolled epidemics. We present an implementation of this method for a common class of compartmental models (e.g. SIR models), and its application in a simple SIR model. Results illustrate how, at the cost of some computation time, this method substantially narrows confidence intervals and avoids nonsensical inferences.
This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.
Using models to provide rapid programme support for California's efforts to suppress Huanglongbing disease of citrus
Authors: McRoberts Neil , Figuera Sara Garcia , Olkowski Sandra , McGuire Brianna , Luo Weiqi , Posny Drew , Gottwald Tim 
Published: May 2019

We describe a series of operational questions posed during the state-wide response in California to the arrival of the invasive citrus disease Huanglongbing. The response is coordinated by an elected committee from the citrus industry and operates in collaboration with the California Department of Food and Agriculture, which gives it regulatory authority to enforce the removal of infected trees. The paper reviews how surveillance for disease and resource allocation between detection and delimitation have been addressed, based on epidemiological principles. In addition, we describe how epidemiological analyses have been used to support rule-making to enact costly but beneficial regulations and we highlight two recurring themes in the programme support work: (i) data are often insufficient for quantitative analyses of questions and (ii) modellers and decision-makers alike may be forced to accept the need to make decisions on the basis of simple or incomplete analyses that are subject to considerable uncertainty.This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’. This theme issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’.
A Kuramoto model of self-other integration across interpersonal synchronization strategies
Authors: Heggli O.A. , Cabral J. , Konvalinka I. , Vuust P. , Kringelbach M.L. 
Published: May 2019

AbstractHuman social behaviour is complex, and the biological and neural mechanisms underpinning it remain debated1,2. A particularly interesting social phenomenon is our ability and tendency to fall into synchrony with other humans3,4. Our ability to coordinate actions and goals relies on the ability to distinguish between and integrate self and other, which when impaired can lead to devastating consequences. Interpersonal synchronization has been a widely used framework for studying action coordination and self-other integration, showing that in simple interactions, such as joint finger tapping, complex interpersonal dynamics emerge. Here we propose a computational model of self-other integration via within- and between-person action-perception links, implemented as a simple Kuramoto model with four oscillators. The model abstracts each member of a dyad as a unit consisting of two connected oscillators, representing intrinsic processes of perception and action. By fitting this model to data from two separate experiments we show that interpersonal synchronization strategies rely on the relationship between within- and between-unit coupling. Specifically, mutual adaptation exhibits a higher between-unit coupling than within-unit coupling; leading-following requires that the follower unit has a low within-unit coupling; and leading-leading occurs when two units jointly exhibit a low between-unit coupling. These findings are consistent with the theory of interpersonal synchronization emerging through self-other integration mediated by processes of action-perception coupling4. Hence, our results show that chaotic human behaviour occurring on a millisecond scale can be modelled using coupled oscillators.
Microbial evolution reshapes soil carbon feedbacks to climate change
Authors: Abs Elsa , Saleska Scott R. , Ferriere Regis 
Published: May 2019

AbstractMicrobial decomposition of soil organic matter is a key component of the global carbon cycle. As Earth’s climate changes, the response of microbes and microbial enzymes to rising temperatures will largely determine the soil carbon feedback to atmospheric CO2. However, while increasing attention focuses on physiological and ecological mechanisms of microbial responses, the role of evolutionary adaptation has been little studied. To address this gap, we developed an ecosystem-evolutionary model of a soil microbe-enzyme system under warming. Constraining the model with observations from five contrasting sites reveals evolutionary aggravation of soil carbon loss to be the most likely outcome; however, temperature-dependent increases in mortality could cause an evolutionary buffering effect instead. We generally predict a strong latitudinal pattern, from small evolutionary effects at low latitude to large evolutionary effects at high latitudes. Accounting for evolutionary mechanisms will likely be critical for improving projections of Earth system responses to climate change.
Increasing plant group productivity through latent genetic variation for cooperation
Authors: Wuest Samuel E. , Pires Nuno D. , Luo Shan , Vasseur Francois , Messier Julie , Grossniklaus Ueli , Niklaus Pascal A. 
Published: May 2019

AbstractHistoric yield advances in the major crops have to a large part been achieved by selection for improved productivity of groups of plant individuals such as high-density stands. Research suggests that such improved group productivity depends on “cooperative” traits (e.g. erect leaves, short stems) that – while beneficial to the group – decrease individual fitness under competition. This poses a problem for some traditional breeding approaches, especially when selection occurs at the level of individuals, because “selfish” traits will be selected for and reduce yields in high-density monocultures. One approach therefore has been to select individuals based on ideotypes with traits expected to promote group productivity. However, this approach is limited to architectural and physiological traits whose effects on growth and competition are relatively easy to anticipate.Here, we developed a general and simple method for the discovery of alleles promoting cooperation in plant stands. Our method is based on the game-theoretical premise that alleles increasing cooperation incur a cost to the individual but benefit the monoculture group. Testing the approach using the model plant Arabidopsis thaliana, we found a major effect locus where the rarer allele was associated with increased cooperation and productivity in high-density stands. The allele likely affects a pleiotropic gene, since we find that it is also associated with reduced root competition but higher resistance against disease. Thus, even though cooperation is considered evolutionarily unstable, conflicting selective forces acting on a pleiotropic gene might maintain latent genetic variation for it in nature. Such variation, once identified in a crop, could be rapidly leveraged in modern breeding programs and provide efficient routes to increase yields.
Caffeine-dependent changes of sleep-wake regulation: evidence for adaptation after repeated intake
Authors: Weibel Janine , Lin Yu-Shiuan , Landolt Hans-Peter , Garbazza Corrado , Kolodyazhniy Vitaliy , Kistler Joshua , Rehm Sophia , Rentsch Katharina , Borgwardt Stefan , Cajochen Christian , Reichert Carolin 
Published: May 2019

AbstractTo enhance wakefulness, daily consumption of caffeine in the morning and afternoon is highly common. However, it is unknown whether such a regular intake pattern affects timing and quality of wakefulness, as regulated by an interplay of circadian and sleep-homeostatic mechanisms. Thus, we investigated the effects of daily caffeine intake and its withdrawal on circadian rhythms and wake-promotion in 20 male young habitual caffeine consumers. We applied a double-blind, within-subject design with a caffeine (150 mg, 3 x daily), a placebo, and a withdrawal condition each lasting ten days. Starting on day nine of treatment, salivary melatonin and cortisol, evening nap sleep, as well as sleepiness and vigilance performance throughout day and night were quantified during 43 h under controlled laboratory conditions. Neither the time course of melatonin (i.e., onset, amplitude, or area under the curve) nor the time course of cortisol were significantly affected by caffeine intake or its withdrawal. During withdrawal, however, volunteers reported increased sleepiness, showed more attentional lapses, as well as polysomnography-derived markers of elevated sleep propensity in the late evening compared to both, placebo and caffeine conditions. Thus, the typical timing of habitual caffeine intake in humans may not necessarily shift circadian phase nor lead to clear-cut benefits in alertness. The time-of-day independent effects of caffeine withdrawal suggest an adaptation to the substance, presumably in the homeostatic aspect of sleep-wake regulation.
Divergent paths to seizure-like events
Authors: Codadu Neela K. , Graham Robert , Burman Richard J. , Jackson-Taylor R. Thomas , Raimondo Joseph V. , Trevelyan Andrew. J. , Parrish R. Ryley 
Published: May 2019

AbstractAimMuch debate exists about how the brain transitions into an epileptic seizure. One source of confusion is that there are likely to be critical differences between experimental seizure models. To address this, we compared the evolving activity patterns in two, widely used, in vitro models of epileptic discharges.MethodsWe compared brain slices, prepared in the same way from young adult mice, that were bathed either in 0 Mg2+, or 100µM 4AP, artificial cerebrospinal fluid.ResultsWe find that while local field potential recordings of epileptiform discharges in the two models appear broadly similar, patch-clamp analysis reveals an important difference in the relative degree of glutamatergic involvement. 4AP affects parvalbumin-expressing interneurons more than other cortical populations, destabilizing their resting state and inducing spontaneous bursting behavior. Consequently, the most prominent pattern of transient discharge (“interictal event”) in this model is almost purely GABAergic, although the transition to seizure-like events (SLEs) involves pyramidal recruitment. In contrast, interictal discharges in 0 Mg2+ are only maintained by a very large glutamatergic component that also involves transient discharges of the interneurons. Seizure-like events in 0 Mg2+ have significantly higher power in the high gamma frequency band (60-120Hz) than these events do in 4AP, and are greatly delayed in onset by diazepam, unlike 4AP events.ConclusionsThe 0 Mg2+ and 4AP models display fundamentally different levels of glutamatergic drive, demonstrating how ostensibly similar pathological discharges can arise from different sources. We contend that similar interpretative issues will also be relevant to clinical practice.
Regulation of theErythrobacter litoralisDSM 8509 general stress response by visible light
Authors: Fiebig Aretha , Varesio Lydia M. , Navarreto Xiomarie Alejandro , Crosson Sean 
Published: May 2019

SUMMARYExtracytoplasmic function (ECF) sigma factors are a major class of environmentally-responsive transcriptional regulators. InAlphaproteobacteriathe ECF sigma factor, σEcfG, activates general stress response (GSR) transcription and protects cells from multiple stressors. A phosphorylation-dependent protein partner switching mechanism, involving HWE/HisKA_2-family histidine kinases, underlies σEcfGactivation. The identity of these sensor kinases and the signals that regulate them remain largely uncharacterized. We have developed the aerobic anoxygenic photoheterotrophic (AAP) bacterium,Erythrobacter litoralisDSM 8509, as a comparative genetic model to investigate GSR regulation. Using this system, we sought to define the contribution of visible light and a photosensory HWE kinase, LovK, to GSR transcription. We identified three HWE kinases that collectively regulate GSR:gsrKandlovKare activators, whilegsrPis a repressor. GSR transcription is higher in the dark than light, and the opposing activities ofgsrKandgsrPare sufficient to achieve light-dependent differential transcription. In the absence ofgsrKandgsrP,lovKalone is sufficient to regulate GSR transcription in response to light. This regulation requires a photochemically active LOV domain in LovK. Our studies establish a role for visible light and HWE kinases in light-dependent regulation of GSR transcription inE. litoralis, an AAP species.GRAPHICAL ABSTRACTABBREVIATED SUMMARYGeneral stress response (GSR) systems protect bacteria from a diverse range of physical and chemical stressors. We have developedErythrobacter litoralisas a new genetic model to study GSR inAlphaproteobacteriaand show that three HWE-family histidine kinases collectively regulate GSR transcription via σEcfG. Visible light is a GSR regulatory signal inE. litoralis, and LovK is a blue-light photosensor kinase that functions as a dark activated GSR regulator.
Creatine transporter knockout mice (Slc6a8) show increases in serotonin-related proteins and are resilient to learned helplessness
Authors: Abdulla Zuhair I. , Pennington Jordan L. , Gutierrez Arnold , Skelton Matthew R. 
Published: May 2019

AbstractApproximately 20% of adults in the U.S. will experience an affective disorder during their life. While it is well established that serotonin (5-HT) is a crucial factor in mood, impaired cellular bioenergetics are also implicated. Creatine (Cr), through the Cr/Phospho-Cr (PCr) shuttle, maintains high ATP concentrations in the neuron. This system may be implicated in the etiology of affective disorders, as reduced Cr, PCr, and ATP are often seen in the brains of affected patients. To address this issue, Cr transporter (Crt) deficient male mice (Slc6a8−/y) and female mice heterozygous for Crt expression (Slc6a8+/−) were used to evaluate how a Cr deficient system would alter affective-like behaviors. Slc6a8−/y and Slc6a8+/− mice had more escapes and faster escape latencies in learned helplessness, indicating a potential resilience to behavioral despair. Elevated zero maze and tail-suspension test performance matched that of wildtype mice, however. Slc6a8−/y mice have increased 5-hydroxyindoleacetic acid content in the hippocampus and striatum and increased monoamine oxidase protein and tryptophan hydroxylase-2 protein content in the hippocampus, while serotonin levels are unchanged. This indicates an increase in 5-HT turnover. Our results indicate that Cr plays a complex role in affective disorders and 5-HT neurotransmission, warranting further investigation.
Simple rules govern the diversity of bacterial nicotianamine-like metallophores
Authors: Laffont Clémentine , Brutesco Catherine , Hajjar Christine , Cullia Gregorio , Fanelli Roberto , Ouerdane Laurent , Cavelier Florine , Arnoux Pascal 
Published: May 2019

ABSTRACTIn metal-scarce environments, some pathogenic bacteria produce opine-type metallophores mainly to face the host’s nutritional immunity. This is the case of staphylopine, pseudopaline and yersinopine, identified inStaphylococcus aureus,Pseudomonas aeruginosaandYersinia pestisrespectively. These metallophores are synthesized by two (CntLM) or three enzymes (CntKLM), CntM catalyzing the last step of biosynthesis using diverse substrates (pyruvate or α-ketoglutarate), pathway intermediates (xNA or yNA) and cofactors (NADH or NADPH), depending on the species. Here, we explored substrate specificity of CntM by combining bioinformatics and structural analysis with chemical synthesis and enzymatic studies. We found that NAD(P)H selectivity was mainly due to the amino acid at position 33 (S. aureusnumbering) which ensures a preferential binding to NADPH when it is an arginine. Moreover, whereas CntM fromP. aeruginosapreferentially uses yNA over xNA, the staphylococcal enzyme is not stereospecific. Most importantly, selectivity towards α-ketoacids is largely governed by a single residue at position 150 of CntM (S. aureusnumbering): an aspartate at this position ensures selectivity towards pyruvate whereas an alanine leads to the consumption of both pyruvate and α-ketoglutarate. Modifying this residue inP. aeruginosaled to a complete reversal of selectivity. Thus, opine-type metallophore diversity is mainly mediated by the absence/presence of acntKgene encoding a histidine racemase, and the presence of an aspartate/alanine at position 150 of CntM. These two simple rules predict the production of a fourth metallophore byPaenibacillus mucilaginosus, which was confirmedin vitroand called bacillopaline.
BiocPkgTools: Toolkit for Mining the Bioconductor Package Ecosystem
Authors: Su Shian , Carey Vincent J. , Shepherd Lori , Ritchie Matthew , Morgan Martin T. , Davis Sean 
Published: May 2019

AbstractMotivationThe Bioconductor project, a large collection of open source software for the comprehension of large-scale biological data, continues to grow with new packages added each week, motivating the development of software tools focused on exposing package metadata to developers and users. The resulting BiocPkgTools package facilitates access to extensive metadata in computable form covering the Bioconductor package ecosystem, facilitating downstream applications such as custom reporting, data and text mining of Bioconductor package text descriptions, graph analytics over package dependencies, and custom search approaches.ResultsThe BiocPkgTools package has been incorporated into the Bioconductor project, installs using standard procedures, and runs on any system supporting R. It provides functions to load detailed package metadata, longitudinal package download statistics, package dependencies, and Bioconductor build reports, all in “tidy data” form. BiocPkgTools can convert from tidy data structures to graph structures, enabling graphbased analytics and visualization. An end-user-friendly graphical package explorer aids in task-centric package discovery. Full documentation and example use cases are included.AvailabilityThe BiocPkgTools software and complete documentation are available from Bioconductor (https://bioconductor.org/packages/BiocPkgTools).
Inferred microbial networks lack replicability: consequences for next-generation biomonitoring
Authors: Pauvert Charlie , Vallance Jessica , Delière Laurent , Bohan David A. , Buée Marc , Vacher Corinne 
Published: May 2019

AbstractPlant-associated microbial interaction networks protect plants against disease. There is, therefore, a need to monitor in real time their responses to environmental changes to predict disease risk and adjust crop protection strategies. Next-Generation Biomonitoring (NGB) proposes to reconstruct automatically these networks from metabarcoding data, to complement ecological community properties commonly used for ecosystem health assessment. This study aimed to evaluate the benefits and shortcomings of community-level and network-level properties for biomonitoring. We specifically investigated whether microbial networks inferred from metabarcoding data show robust responses to agricultural practices, using the grapevine microbiota as a study system. Our results demonstrate a strong footprint of the agricultural practice on the metabarcoding data, when analyzed at the community level. The richness, diversity and evenness of fungal communities were significantly higher in organic than conventional plots. The cropping system also affected the composition of grapevine foliar fungal communities significantly. Contrary to our expectations, microbial networks were less sensitive to changes in agricultural practices than microbial communities, confirming that NGB should not only consider network-level properties but also community-level properties. Moreover, we found that microbial networks lacked replicability within a cropping system but that consensus networks, built from several network replicates, could generate relevant hypotheses of microbial interactions. As things stand, community-level properties appear to be a more reliable and statistically powerful monitoring option than network-level properties. Future developments, especially in network inference methods, are likely to challenge our findings and help to improve the monitoring of the ecosystem services provided by the plant microbiota.
Spatiotemporal limits of optogenetic manipulations in cortical circuits
Authors: Li Nuo , Chen Susu , Guo Zengcai V. , Chen Han , Huo Yan , Inagaki Hidehiko K. , Davis Courtney , Hansel David , Guo Caiying , Svoboda Karel 
Published: May 2019

AbstractNeuronal inactivation is commonly used to assess the involvement of groups of neurons in specific brain functions. Optogenetic tools allow manipulations of genetically and spatially defined neuronal populations with excellent temporal resolution. However, the targeted neurons are coupled with other neural populations over multiple length scales. As a result, the effects of localized optogenetic manipulations are not limited to the targeted neurons, but produces spatially extended excitation and inhibition with rich dynamics. Here we benchmarked several optogenetic silencers in transgenic mice and with viral gene transduction, with the goal to inactivate excitatory neurons in small regions of neocortex. We analyzed the effects of the perturbations in vivo using electrophysiology. Channelrhodopsin activation of GABAergic neurons produced more effective photoinhibition of pyramidal neurons than direct photoinhibition using light-gated ion pumps. We made transgenic mice expressing the light-dependent chloride channel GtACR under the control of Cre-recombinase. Activation of GtACR produced the most potent photoinhibition. For all methods, localized photostimuli produced photoinhibition that extended substantially beyond the spread of light in tissue, although different methods had slightly different resolution limits (radius of inactivation, 0.5 mm to 1 mm). The spatial profile of photoinhibition was likely shaped by strong coupling between cortical neurons. Over some range of photostimulation, circuits produced the “paradoxical effect”, where excitation of inhibitory neurons reduced activity in these neurons, together with pyramidal neurons, a signature of inhibition-stabilized neural networks. The offset of optogenetic inactivation was followed by rebound excitation in a light dose-dependent manner, which can be mitigated by slowly varying photostimuli, but at the expense of time resolution. Our data offer guidance for the design of in vivo optogenetics experiments and suggest how these experiments can reveal operating principles of neural circuits.