bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incorporating genetic selection into individual-based models (IBMs) of malaria and other infectious diseases
Authors: Hastings Ian M. , Sharma Raman 
Published: October 2019

AbstractOptimal control strategies for human infections are often investigated by computational approaches using individual-based models (IBMs). These typically track humans and evaluate the impact of control interventions in terms of human deaths, clinical cases averted, interruption of transmission etc. Genetic selection can be incorporated into these IBMs and used to track the spread of mutations whose origin and spread are often driven by the intervention, and which subsequently undermine the control strategy; for example, mutations which encode antimicrobial drug resistance or diagnosis- or vaccine-escape phenotypes. Basic population genetic descriptions of selection are based on infinite population sizes (so that chance fluctuations in allele frequency are absent) but IBMs track finite population sizes. We describe how the finite sizes of IBMs affect simulating the dynamics of genetic selection and how best to incorporate genetic selection into these models. We use the OpenMalaria IBM of malaria as an example, but the same principles apply to IBMs of other diseases. We identify four strategies to incorporate selection into IBMs and make the following four recommendations. Firstly, calculate and report the selection coefficients, s, of the advantageous allele as the key genetic parameter. Secondly, use these values of ‘s’ to calculate the wait-time until a mutation successful establishes itself in the population. The wait time for the mutation can be added to speed of selection, s, to calculate when the mutation will reach significant, operationally important levels. Thirdly, quantify the ability of the IBM to robustly estimate small selection coefficients. Fourthly, optimise computational efficacy: when ‘s’ is small it is plausible that fewer replicates of larger IBMs will be more efficient than a larger number of replicates of smaller size.
The Arabidopsis R-SNARE VAMP714 is essential for polarization of PIN proteins in the establishment and maintenance of auxin gradients
Authors: Gu Xiaoyan , Fonseka Kumari , Casson Stuart A. , Smertenko Andrei , Guo Guangqin , Topping Jennifer F. , Hussey Patrick J. , Lindsey Keith 
Published: October 2019

SummaryThe plant hormone auxin and its directional intercellular transport plays a major role in diverse aspects of plant growth and development. The establishment of auxin gradients in plants requires asymmetric distribution of members of the auxin efflux carrier PIN-FORMED (PIN) protein family to the plasma membrane. An endocytic pathway regulates the recycling of PIN proteins between the plasma membrane and endosomes, providing a mechanism for dynamic localization.N-ethylmaleimide-sensitive factor adaptor protein receptors (SNAP receptors, SNAREs) mediate fusion between vesicles and target membranes and are classed as Q- or R-SNAREs based on their sequence. We analysed gain- and loss-of-function mutants, dominant negative transgenics and protein localization of the Arabidopsis R-SNARE VAMP714 to understand its function.We demonstrate that VAMP714 is essential for the insertion of PINs into the plasmamembrane, for polar auxin transport, and for root gravitropism and morphogenesis.VAMP714gene expression is upregulated by auxin, and the VAMP714 protein co-localizes with ER and Golgi vesicles and with PIN proteins at the plasma membrane.It is proposed that VAMP714 mediates the delivery of PIN-carrying vesicles to the plasma membrane, and that this forms part of a positive regulatory loop in which auxin activates a VAMP714-dependent PIN/auxin transport system to control development.
A Recurrent Neural Network Based Method for Genotype Imputation on Phased Genotype Data
Authors: Kojima Kaname , Tadaka Shu , Katsuoka Fumiki , Tamiya Gen , Yamamoto Masayuki , Kinoshita Kengo 
Published: October 2019

AbstractGenotype imputation estimates genotypes of unobserved variants from genotype data of other observed variants, and such estimation is enabled using haplotype data of a large number of other individuals. Although existing imputation methods explicitly use haplotype data, the accessibility of haplotype data is often limited because the agreement is necessary from donors of genome data. We propose a new imputation method that uses bidirectional recurrent neural network, and haplotype data of a large number of individuals are encoded as its model parameters through the training step, which can be shared publicly due to the difficulty in restoring genotype data at the individual-level. In the performance evaluation using the phased genotype data in the 1000 Genomes Project, the imputation accuracy of the proposed method inR2is comparative with existing methods for variants with MAF ≥ 0.05 and is slightly worse than those of the existing methods for variants with MAF < 0.05. In a scenario of limited availability of haplotype data to the existing methods, the accuracy of the proposed method is higher than those of the existing methods at least for variants with MAF ≥ 0.005. Python code of our implementation for imputation is available athttps://github.com/kanamekojima/rnnimp/.
Pre-adaptation to climate change through topography-driven evolution of traits and their plasticity
Authors: De Kort H. , Panis B. , Janssens S.B. , Helsen K. , Honnay O. 
Published: October 2019

ABSTRACTClimate change is expected to increase the level of drought stress experienced by many plant populations, yet the spatial distribution of changes in dryness remains highly uncertain. Species can, to some extent, adapt to climate uncertainty through evolving increased trait plasticity. Biodiversity conservation could capitalize on such natural variation in the ability of populations to cope with climate variability. Yet, disentangling evolution of trait means vs. trait plasticity is challenging, as it requires a sampling design with genetic replicates grown under distinct environmental conditions. Here, we applied different soil moisture treatments to clones of Fragaria vesca plants that were raised from seeds that were sampled in distinct mountainous topographical settings, to study adaptive trait and plasticity divergence in response to drought. We demonstrate that various fitness traits evolved along topographical gradients, including increased specific leaf area (SLA) with increasing slope, and increased growth plasticity with increasing altitude. Our results indicate that traits and their plasticity can evolve independently in response to distinct topographical stressors. We further show that trait heritability varies considerably among traits and topographical settings. Heritability of phenotypic plasticity tended to increase with altitude for all traits, with populations from high altitudes harboring more than twice the heritability for growth and SLA plasticity compared to populations from low altitudes. We conclude that (i) low altitudinal populations, which are expected to be least vulnerable to climate change, may only withstand limited increases in drought stress, while (ii) populations that evolved to thrive under more heterogeneous mountain conditions are pre-adapted to climate change through high plasticity and heritability. Highly heterogeneous landscapes may thus represent invaluable sources of quantitative genetic variation that could support conservation under climate change across the globe.
Heterogeneity in heat shock response dynamics caused by translation fidelity decline and proteostasis collapse
Authors: Vertti-Quintero Nadia , Berger Simon , Casadevall i Solvas Xavier , Statzer Cyril , Annis Jillian , Ruppen Peter , Stavrakis Stavros , Ewald Collin Y. , Gunawan Rudiyanto , deMello Andrew 
Published: October 2019

AbstractGenetics, environment, and stochasticity influence the rate of ageing in living organisms. Individual Caenorhabditis elegans that are genetically identical and cultured in the same environment have different lifespans, suggesting a significant role of stochasticity in ageing. We have developed a novel microfluidic methodology to measure heat-shock response as a surrogate marker for heterogeneity associated with lifespan and have quantified the heat-shock response of C. elegans at the population, single individual, and tissue levels. We have further mathematically modelled our data to identify the major drivers determining such heterogeneity. This approach demonstrates that protein translation and degradation rate constants explain the individuality of the heat-shock time-course dynamic. We observed a decline of protein turnover capacity in early adulthood, co-incidentally occurring as the predicted proteostasis collapse. We identified a decline of intestinal response as the tissue that underlies the individual heterogeneity. Additionally, we verified that individuals with enhanced translation fidelity in early adulthood live longer. Altogether, our results reveal that the stochastic onset of proteostasis collapse of somatic tissues during early adulthood reflects individual protein translation capacity underlying heterogenic ageing of isogenic C. elegans.
The inactivation of enzymes belonging to the central carbon metabolism, a novel mechanism of developing antibiotic resistance
Authors: Gil-Gil Teresa , Corona Fernando , Martínez José Luis , Bernardini Alejandra 
Published: October 2019

AbstractFosfomycin is a bactericidal antibiotic, analogous to phosphoenolpyruvate (PEP) that exerts its activity by inhibiting the activity of MurA. This enzyme catalyzes the first step of peptidoglycan biosynthesis, the transfer of enolpyruvate from PEP to uridine-diphosphate-N-acetylglucosamine. Fosfomycin is increasingly used in the last years, mainly for treating infections caused by Gram-negative multidrug resistant bacteria asStenotrophomonas maltophilia, an opportunistic pathogen characterized by its low susceptibility to antibiotics of common use. The mechanisms of mutational resistance to fosfomycin inS. maltophiliawere studied in the current work. None of the mechanisms so far described for other organisms, which include the production of fosfomycin inactivating enzymes, target modification, induction of alternative peptidoglycan biosynthesis pathway and the impaired entrance of the antibiotic, are involved in the acquisition of such resistance by this bacterial species. Rather the unique cause of resistance in the studied mutants is the mutational inactivation of different enzymes belonging to the Embden-Meyerhof-Parnas central metabolism pathway. The amount of intracellular fosfomycin accumulation did not change in any of these mutants showing that neither the inactivation nor the transport of the antibiotic were involved. Transcriptomic analysis also showed that the mutants did not present changes in the expression level of putative alternative peptidoglycan biosynthesis pathway genes neither any related enzyme. Finally, the mutants did not present an increased PEP concentration that might compete with fosfomycin for its binding to MurA. Based on these results, we describe a completely novel mechanism of antibiotic resistance based on the remodeling ofS. maltophiliametabolism.SignificanceAntibiotic resistance (AR) has been largely considered as a specific bacterial response to an antibiotic challenge. Indeed, its study has been mainly concentrated in mechanisms that affect the antibiotics (mutations in transporters, the activity of efflux pumps and antibiotic modifying enzymes) or their targets (i.e.: target mutations, protection or bypass). Usually, AR-associated metabolic changes were considered to be a consequence (fitness costs) and not a cause of AR. Herein, we show that strong alterations in the bacterial metabolism can also be the cause of AR. In the study here presented,Stenotrophomonas maltophiliaacquires fosfomycin resistance through the inactivation of glycolytic enzymes belonging to the Embden-Meyerhof-Parnas. Besides resistance to fosfomycin, this inactivation also impairs the bacterial gluconeogenic pathway. Together with previous work showing that AR can be under metabolic control, our results provide evidence that AR is intertwined with the bacterial metabolism.
Using Unmanned Aerial Vehicles (UAV) for free-roaming dog population size estimation
Authors: Warembourg Charlotte , Berger-González Monica , Alvarez Danilo , Sousa Filipe Maximiano , Hernández Alexis López , Roquel Pablo , Eyermann Joe , Benner Merlin , Dürr Salome 
Published: October 2019

AbstractPopulation size estimation is performed for several reasons including disease surveillance and control, for example to design adequate control strategies such as vaccination programs or to estimate a vaccination campaign coverage. In this study, we aimed at assessing the benefits and challenges of using Unmanned Aerial Vehicles (UAV) to estimate the size of free-roaming domestic dog (FRDD) populations and compare the results with two regularly used methods for population estimations: a Bayesian statistical model based on capture-recapture data and the human:dog ratio estimation. Three studies sites of one square kilometer were selected in Petén department, Guatemala. UAV flight were conducted twice during two consecutive days per study site. The UAV’s camera was set to regularly take pictures and cover the entire surface of the selected areas. A door-to-door survey was conducted in the same areas, all available dogs were marked with a collar and owner were interviewed. Simultaneously to the UAV’s flight, transect walks were performed and the number of collared and non-collared dogs were recorded. Data collected during the interviews and the number of dogs counted during the transect walks informed a Bayesian statistical model. The number of dogs counted on the UAV’s pictures and the estimates given by the Bayesian statistical model, as well as the estimates derived from using a 5:1 human:dog ratio were compared to dog census data. FRDD could be detected using the UAV’s method. However, the method lacked of sensitivity, which could be overcome by choosing the flight timing and the study area wisely, or using infrared camera or automatic detection of the dogs. We also suggest to combine UAV and capture-recapture methods to obtain reliable FRDD population size estimated. This publication may provide helpful directions to design dog population size estimation methods using UAV.
The intrinsic neonatal hippocampal network: rsfMRI findings
Authors: Howell Athena L. , Osher David E. , Li Jin , Saygin Zeynep M. 
Published: October 2019

AbstractMany adults cannot voluntarily recall memories before the ages of 3-5, a phenomenon referred to as “infantile amnesia” The development of the hippocampal network likely plays a significant part in the emergence of the ability to form long-lasting memories. In adults, the hippocampus has specialized and privileged connections with certain cortical networks, which presumably facilitate its involvement in memory encoding, consolidation, and retrieval. Is the hippocampus already specialized in these cortical connections at birth? And are the topographical principles of connectivity (e.g. long-axis specialization) present at birth? We analyzed resting-state hippocampal connectivity in neonates scanned within one week of birth (Developmental Human Connectome Project) and compared them to adults (Human Connectome Project). We explored the connections of the whole hippocampus and its long-axis specialization to seven canonical cortical networks. We found that the neonatal hippocampal networks show clear immaturity at birth: adults showed hippocampal connectivity that was unique for each cortical network, whereas neonates showed no differentiation in hippocampal connectivity across these networks. Further, neonates lacked long-axis specialization (i.e., along anterior-posterior axis) of the hippocampus in its differential connectivity patterns to the cortical networks. This immaturity in connectivity may contribute to immaturity in memory formation in the first years of life.“New and Noteworthy”While animal data, and anatomical and behavioral human data from young children suggest that the hippocampus is immature at birth, to date, there are no direct assessments of human hippocampal functional connectivity (FC) very early in life. Our study explores the FC of the hippocampus to the cortex at birth, allowing insight into the development of human memory systems.
Brain functional connectivity correlates of response in the 7.5% CO2inhalational model of generalized anxiety disorder: a pilot study
Authors: Huneke Nathan T.M. , Broulidakis M. John , Darekar Angela , Baldwin David S. , Garner Matthew 
Published: October 2019

AbstractThe 7.5% CO2inhalational model (‘CO2challenge’) can be used to explore potential treatments for generalized anxiety disorder. However, it remains unknown how inter-individual variability in the functional architecture of negative affective valence systems might relate to the anxiogenic response to CO2challenge. In this pilot study, we explored how connectivity in systems associated with processing potential threat (“anxiety”) correlated with behavioural measures of anxiety following prolonged CO2inhalation.The negative affective valence system was identified using a passive emotional face perception task. Spherical regions of interest were created from peak voxels of significant brain activation when 100 young adult participants viewed emotional faces compared with black and white concentric circles during a functional MRI scan. Using these regions of interest, generalized psychophysiological interaction (gPPI) analysis was undertaken to explore task-evoked functional connectivity in a separate group of 13 healthy volunteers. Within 7 days of the scan, these participants underwent CO2challenge and results from the gPPI analysis were correlated with CO2outcome measures.Exposure to CO2challenge significantly increased subjective anxiety, negative affect, systolic blood pressure and heart rate. Functional connectivity between the ventromedial prefrontal cortex and right amygdala was positively correlated with heart rate. Increased connectivity between the vmPFC and the right amygdala, and decreased connectivity between the midcingulate cortex (MCC) and the left amygdala, correlated with subjective anxiety during CO2challenge.Response to CO2challenge was related to task-evoked functional connectivity between regions known to be important in processing potential threat. Further studies are required to assess whether this translates into clinical populations. Measures of functional connectivity within emotional processing networks could be potential biomarkers to enable stratification of healthy volunteers, and to examine correlates of response, in trials using experimental medicine models.
Steering Molecular Dynamics Simulations of Membrane-Associated Proteins with Neutron Reflection Results
Authors: Treece Bradley W. , Heinrich Frank , Ramanathan Arvind , Lösche Mathias 
Published: October 2019

AbstractWe present a method to incorporate structural results from neutron reflectometry, a technique that determines interfacial structures such as protein-membrane complexes at a solid surface, into molecular dynamics simulations. By analyzing component volume occupancy profiles, which describe the one-dimensional distribution of a particular molecular component within an interfacial architecture, we construct a real-space constraint in the form of a biasing potential for the simulation that vanishes when the simulated and experimental profiles agree. This approach improves the correspondence between simulation and experiment, as shown for an earlier investigation where an NR-derived structure was well captured by an independent MD simulation, and may lead to faster equilibration of ensemble structures. We further show that time averaging of the observable when biasing with this approach permits fluctuations about the average, which are necessary for conformational exploration of the protein. The method described here also provides insights into systems that are characterized by NR and MD when the two show slight differences in their profiles. This is particularly valuable for studies of proteins at interfaces that contain disordered regions since the conformation of such regions is difficult to judge from the analysis of one-dimensional experimental profiles and take prohibitively long to equilibrate in simulations.
Cortical functional connectivity indexes arousal state during sleep and anesthesia
Authors: Banks Matthew I. , Krause Bryan M. , Endemann Christopher M. , Campbell Declan I. , Kovach Christopher K. , Dyken M. Eric , Kawasaki Hiroto , Nourski Kirill V. 
Published: October 2019

AbstractDisruption of cortical connectivity likely contributes to loss of consciousness (LOC) during both sleep and general anesthesia, but the degree of overlap in the underlying mechanisms is unclear. Both sleep and anesthesia comprise states of varying levels of arousal and consciousness, including states of largely maintained consciousness (sleep: N1, REM; anesthesia: sedated but responsive) as well as states of substantially reduced consciousness (sleep: N2/N3; anesthesia: unresponsive). Here, we tested the hypotheses that (1) cortical connectivity will reflect clear changes when transitioning into states of reduced consciousness, and (2) these changes are similar for arousal states of comparable levels of consciousness during sleep and anesthesia. Using intracranial recordings from five neurosurgical patients, we compared resting state cortical functional connectivity (as measured by weighted phase lag index) in the same subjects across arousal states during natural sleep [wake (WS), N1, N2, N3, REM] and propofol anesthesia [pre-drug wake (WA), sedated/responsive (S) and unresponsive (U)]. In wake states WS and WA, alpha-band connectivity within and between temporal, parietal and occipital regions was dominant. This pattern was largely unchanged in N1, REM and S. Transitions into states of reduced consciousness N2, N3 and U were characterized by dramatic and strikingly similar changes in connectivity, with dominant connections shifting to frontal cortex. We suggest that shifts from temporo-parieto-occipital to frontal cortical connectivity may reflect impaired sensory processing in states of reduced consciousness. The data indicate that functional connectivity can serve as a biomarker of arousal state and suggest common mechanisms of LOC in sleep and anesthesia.
Hypoxia inducible factor-2α increases sensitivity of colon cancer cells towards oxidative cell death
Authors: Singhal Rashi , Mitta Sreedhar R , Olive Kenneth P. , Lyssiotis Costas A. , Shah Yatrik M. 
Published: October 2019

AbstractColorectal cancer (CRC) is the second leading cause of cancer-related deaths in the US. Hypoxia is a hallmark of solid tumors which promotes tumor cell growth, survival, metastasis and confers resistance to chemo and radiotherapies. Targeting hypoxic cells has been difficult. Moreover, inhibitors for the major transcription factors, hypoxia inducible factor (HIF)-1α and HIF-2α have not shown long-term efficacy in most cancers. We have previously shown that HIF-2α is essential for colon tumorigenesis. Using an unbiased screen, we show a significant increase in synthetic lethality of HIF-2α overexpressing tumor enteroids to oxidative cell death activators. The treatment with hypoxia mimetic FG4592 (Roxadustat), led to a robust increase in erastin-, RSL3-, and dimethyl fumarate-induced cell death in a dose- and time-dependent manner. Further, our in-vitro data shows that HIF-2α knock-down cells are completely resistant to these drugs. HIF activation promotes upregulation of lipid synthesis genes in vitro and in vivo leading to oxidative stress. Taken together, our results suggest that this intrinsic sensitivity towards oxidative stress associated with hypoxia could be utilized as a persistent and dynamic form of cell death for colon cancer treatment.