bluuebunny/crossref_metadata_2025_split huggingface dataset:
Transcriptional regulatory mechanisms of fibrosis development in mouse lung tissue exposed to carbon nanotubes
Authors: Zhernovkov Vadim , Santra Tapesh , Cassidy Hilary , Rukhlenko Oleksii , Matallanas David , Krstic Aleksandar , Kolch Walter , Lobaskin Vladimir , Kholodenko Boris N. 
Published: July 2018

AbstractBackgroundCarbon nanotubes (CNTs) usage has rapidly increased in the last few decades due to their unique properties, exploited in various industrial and commercial products. Certain types of CNTs cause adverse health effects, including chronic inflammation and fibrosis. Despite the large number of in vitro and in vivo studies evaluating these effects, many important questions remain unanswered due to a lack of mechanistic understanding of how CNTs induce cellular stress responses. In order to predict CNT toxicity, it is important to understand which transcriptional programs are specifically activated in response to CNTs, and what similarities and differences exist in relation to other toxic inducers exerting similar adverse effects.ResultsA systems biology approach was applied to reveal complex interactions at the molecular level in mouse lung tissue in response to different fibrosis inducers: two types of multi-walled CNTs, NM-401 and NRCWE-26, and bleomycin (BLM). Based on mRNA gene expression profiles, we inferred gene regulatory networks (GRNs) to capture functional hierarchical regulatory structures between genes and their regulators. We found that activities of the transcription factors (TFs) Myc, Arid5a and Mxd1 were associated with the regulation of cytokine transcription in response to CNTs, while in response to BLM treatment, Myc was associated with p53 signaling. TF Litaf was identified as the essential regulator for noncanonical signaling of TLR2/4 driven by CNTs. Despite the different nature of the lung injury caused by CNTs and BLM, we identified common stress response modules, that included DNA damage (TFs: E2f8, E2f1, Foxm1), M1/M2 macrophage polarization (TF: Mafb), Interferon response (TFs: Irf7, Stat2 and Irf9) for all agents.ConclusionsThese results suggest that the reconstruction and analysis of TF-centric gene interaction networks can reveal key targets and regulators of cellular stress responses to toxic agents.
Conserved SQ and QS motifs in bacterial effectors suggest pathogen interplay with the ATM kinase family during infection
Authors: Sampietro Davide , Sámano-Sánchez Hugo , Davey Norman E. , Sharan Malvika , Mészáros Bálint , Gibson Toby J. , Kumar Manjeet 
Published: July 2018

AbstractUnderstanding how bacteria hijack eukaryotic cells during infection is vital to develop better strategies to counter the pathologies that they cause. ATM kinase family members phosphorylate eukaryotic protein substrates on Ser or Thr residues followed by Gln. The kinases are active under oxidative stress conditions and/or the presence of ds-DNA breaks. While examining the protein sequences of well-known bacterial effector proteins such as CagA and Tir, we noticed that they often show conserved (S/TQ) motifs, even though the evidence for effector phosphorylation by ATM has not been reported. We undertook a bioinformatics analysis to examine effectors for their potential to mimic the eukaryotic substrates of the ATM kinase. The candidates we found could interfere with the host’s intracellular signaling network upon interaction, which might give an advantage to the pathogen inside the host. Further, the putative phosphorylation sites should be accessible, conserved across species and, in the vicinity to the phosphorylation sites, positively charged residues should be depleted. We also noticed that the reverse motif (QT/S) is often also conserved and located close to (S/TQ) sites, indicating its potential biological role in ATM kinase function. Our findings could suggest a mechanism of infection whereby many pathogens inactivate/modulate the host ATM signaling pathway.
A novel interplay between GEFs orchestrates Cdc42 activity during cell polarity and cytokinesis
Authors: Hercyk Brian S. , Rich-Robinson Julie T. , Mitoubsi Ahmad S. , Harrell Marcus A. , Das Maitreyi E. 
Published: July 2018

ABSTRACTCdc42, a conserved regulator of cell polarity, is activated by two GEFs, Gef1 and Scd1, in fission yeast. Whilegef1andscd1mutants exhibit distinct phenotypes, how they do so is unclear given that they activate the same GTPase. Using the GEF localization pattern during cytokinesis as a paradigm, we report a novel interplay between Gef1 and Scd1 that spatially modulates Cdc42. We find that Gef1 promotes Scd1 localization to the division site during cytokinesis and to the new end during polarized growth through the recruitment of the scaffold Scd2 via a Cdc42 feedforward pathway. Gef1-mediated Scd1 recruitment at the new end enables the transition from monopolar to bipolar growth. Reciprocally, Scd1 restricts Gef1 localization to prevent ectopic Cdc42 activation during cytokinesis to promote cell separation and during interphase to maintain cell shape. Our findings reveal an elegant regulatory pattern in which Gef1 establishes new sites of Scd1-mediated Cdc42 activity, while Scd1 restricts Gef1 to functional sites. We propose that crosstalk between GEFs is a conserved mechanism that orchestrates Cdc42 activation during complex cellular processes.Summary StatementCdc42 GEFs Gef1 and Scd1 crosstalk to fine-tune Cdc42 activity. This crosstalk promotes bipolar growth and maintains cell shape in fission yeast.
Deep learning for inferring gene relationships from single-cell expression data
Authors: Yuan Ye , Bar-Joseph Ziv 
Published: July 2018

AbstractSeveral methods were developed to mine gene-gene relationships from expression data. Examples include correlation and mutual information methods for co-expression analysis, clustering and undirected graphical models for functional assignments and directed graphical models for pathway reconstruction. Using a novel encoding for gene expression data, followed by deep neural networks analysis, we present a framework that can successfully address all these diverse tasks. We show that our method, CNNC, improves upon prior methods in tasks ranging from predicting transcription factor targets to identifying disease related genes to causality inference. CNNC’s encoding provides insights about some of the decisions it makes and their biological basis. CNNC is flexible and can easily be extended to integrate additional types of genomics data leading to further improvements in its performance.Supporting website with software and data:https://github.com/xiaoyeye/CNNC.
Orthogonal Representations of Reward Magnitude, Certainty, and Volatility in the Macaque Orbitofrontal Cortex
Authors: Yang Tianming , Murray Elisabeth A. 
Published: July 2018

AbstractCategorical knowledge about the probabilistic and volatile nature of resource availability can improve foraging strategies, yet we have little understanding of how the brain represents such knowledge. Neurons in the orbitofrontal cortex (OFC) of macaques encode several decision variables (e.g., reward magnitude, probability) that could influence choice behavior. Here we investigated whether OFC neurons also represent two aspects of reward predictability: certainty and volatility. Rhesus monkeys performed a visual stimulus-reward association task in which a set of simple shapes preceded the delivery of reward, and they learned the nature of each shape’s reward association along two dimensions. One involved the certainty of a reward outcome; rewards can be either deterministic (and therefore certain) or probabilistic (uncertain). A second dimension reflected the volatility of an outcome; reward schedules can be either stable over time or volatile. During stimulus presentation, the activity of OFC neurons reflected both categorical certainty and categorical volatility, in addition to reward magnitude. These three characteristics were represented orthogonally by three distinct neural populations of similar size. These findings point to a more general role for OFC in processing reward information than one restricted to encoding parametric valuations such as reward magnitude and probability.
Extensive recoding of dengue virus type 2 specifically reduces replication in primate cells without gain-of-function in Aedes aegypti mosquitoes
Authors: Stauft Charles B. , Shen Sam H. , Song Yutong , Gorbatsevych Oleksandr , Asare Emmanuel , Futcher Bruce , Mueller Steffen , Payne Anne , Brecher Matthew , Kramer Laura , Wimmer Eckard 
Published: July 2018

AbstractDengue virus (DENV), an arthropod-borne (“arbovirus”) virus causing a range of human maladies ranging from self-limiting dengue fever to the life-threatening dengue shock syndrome, proliferates well in two different taxa of the Animal Kingdom, mosquitoes and primates. Unexpectedly, mosquitoes and primates have distinct preferences when expressing their genes by translation, e.g. members of these taxa show taxonomic group-specific intolerance to certain codon pairs. This is called “codon pair bias”. By necessity, arboviruses evolved to delicately balance this fundamental difference in their ORFs. Using the mosquito-borne human pathogen DENV we have undone the evolutionarily conserved genomic balance in its ORF sequence and specifically shifted the encoding preference away from primates. However, this recoding of DENV raised concerns of ‘gain-of-function,’ namely whether recoding could inadvertently increase fitness for replication in the arthropod vector. Using mosquito cell cultures and two strains of Aedes aegypti we did not observe any increase in fitness in DENV2 variants codon pair deoptimized for humans. This ability to disrupt and control an arbovirus’s host preference has great promise towards developing the next generation of synthetic vaccines not only for DENV but for other emerging arboviral pathogens such as chikungunya virus and Zika virus.
A statistical note on the detection of autoassociative dynamics in hippocampal place-cell sequences
Authors: Gönner Lorenz , Vitay Julien , Hamker Fred 
Published: July 2018

AbstractThe sequential activity of hippocampal place cells observed during sleep and awake resting is widely viewed as a neural correlate of memory processes. While recent work has advanced our understanding of the content represented during rest-related place-cell sequences, the nature of hippocampal population dynamics during sequential activity remains poorly understood. A recent experimental study has reported that place-cell sequences show a pattern of step-like movement, reminiscent of transitions between discrete attractor states (Pfeiffer and Foster, 2015). By contrast, previous theoretical models predict that the spatiotemporal structure of place-cell sequences should reflect the disribution of place fields, typically observed to be spatially smooth.Motivated by this discrepancy between models and experimental data, we performed a quantitative comparison between these results and the spike trains generated by a network model for the generation of place-cell sequences (Gönner et al., 2017). Although the model is based on continuous attractor network dynamics, we observed that the movement of sequential place representations was phase-locked to the population oscillation, highly similar to the experimental data interpreted as evidence for discrete attractor dynamics. To resolve this potential contradiction, we performed a detailed analysis of the methodology used to identify discrete attractor dynamics. Our results show that a previous approach to step size decoding is prone to a decoding artefact. We propose a modified approach to estimate step sizes which may help to characterize the underlying circuit dynamics in vivo.
Measuring Orangutan nest structure using Unmanned Aerial Vehicle (UAV) and ImageJ
Authors: Kamaruszaman Salniza Akmar , Fadzly Nik , Abd Mutalib Aini Hasanah , Muslim Aidy M. , Atmoko Sri Suci Utami , Mansor Mashhor , Mansor Asyaf , Rupert Nadine , Zakaria Rahmad , Hashim Zarul Hazrin , Md Sah Amir Shah Ruddin , Jamsari Fadhirul Fitri , Azman Nur Munira 
Published: July 2018

AbstractThe nest is one of the crucial elements in orangutan daily activities. Previously, most of the nest structure studies were done manually by estimating measurement directly from visual observation. However, using the latest unmanned aerial vehicle (UAV) technology, we can reduce the workforce, time and energy while simultaneously ensuring the safety of the researcher conducting nest structure analysis. We recorded 49 pictures of orangutan nests at Sepilok Orangutan Rehabilitation Centre (SORC) using UAV (DJI Phantom 3 Quadcopter). The nest structure (length, depth, and width) was digitally measured by using ImageJ. Most of the nests were built at a strong, stable, and comfortable position at the top of the tree. Most orangutans chose Eusideroxylon zwageri to build nest compared to other tree species because of the strong and durable wood characteristic which would create a sturdy, strong and comfortable nest. We propose the use of drone with digital image analysis could provide a more accurate, less time consuming and safe method for studying orangutan nest structure.
Delayed differentiation of vaginal and uterine microbiomes in dairy cows developing postpartum endometritis
Authors: Miranda-CasoLuengo Raúl , Lu Junnan , Williams Erin J. , Miranda-CasoLuengo Aleksandra A. , Carrington Stephen D. , Evans Alexander C.O. , Meijer Wim G. 
Published: July 2018

AbstractBacterial infection of the uterus is a normal event after parturition. While the healthy cow achieves uterine clearance early postpartum, cows unable to control the infection within 21 days after calving develop postpartum endometritis. Studies on the Microbial Ecology of the bovine reproductive tract have focused on either vaginal or uterine microbiomes. This is the first study that compares both microbiomes in the same animals. Terminal Restriction Fragment Length Polymorphism of the 16S rRNA gene showed that despite large differences associated to individuals, a shared community exist in vagina and uterus during the postpartum period. The largest changes associated with development of endometritis were observed at 7 days postpartum, a time when vaginal and uterine microbiomes were most similar. 16S rRNA Pyrosequencing of the vaginal microbiome at 7 days postpartum showed at least three different microbiome types that were associated with postpartum endometritis. All three microbiome types featured reduced bacterial diversity. Taken together, the above findings support a scenario where disruption of the compartmentalization of the reproductive tract during parturition results in the dispersal and mixing of the vaginal and uterine microbiomes, which subsequently are subject to differentiation. This microbial succession is likely associated to early clearance in the healthy cow. In contrast, loss of bacterial diversity and dominance of the microbiome by few bacterial taxa were related to a delayed succession in cows developing endometritis at 7 DPP.
Young Children Integrate Current Observations, Priors and Agent Information to Build Predictive Models of Others’ Actions
Authors: Kayhan E. , Heil L. , Kwisthout J. , van Rooij I. , Hunnius S. , Bekkering H. 
Published: July 2018

AbstractFrom early on in life, children are able to use information from their environment to form predictions about events. For instance, they can use statistical information about a population to predict the sample drawn from that population and infer an agent’s preferences from systematic violations of random sampling. We investigated how young children build and update models of an agent’s sampling actions over time, and whether a computational model based on the causal Bayesian network formalization of predictive processing can explain this process.We formalized three hypotheses about how different explanatory variables (i.e., prior probabilities, current observations, and agent characteristics) are used to build predictive models of others’ actions. We measured pupillary responses as a behavioral marker of ‘prediction errors’ (i.e., the perceived mismatch between what one’s model of an agent predicts and what the agent actually does), as described in the predictive processing framework. Pupillary responses of 24-month-olds, but not 18-month-olds, showed that young children integrated information about current observations, priors and agents to generate predictive models of agents and their actions.These findings shed light on the mechanisms behind toddlers’ inferences about agent-caused events. To our knowledge, this is the first study in which young children’s pupillary responses are used as markers of prediction errors, and explained by a computational model based on the causal Bayesian network formalization of predictive processing. We argue that the predictive processing framework provides a promising explanation of the way in which young children process other persons’ actions.HighlightsWe present three formalized hypotheses on how young children generate predictive models of others’ sampling actions.We measured pupillary responses of children as a behavioral marker of prediction errors as described in the predictive processing framework.Results showed that young children integrated information about current observations, prior probabilities and agents to generate predictive models about others’ actions.A computational model based on the causal Bayesian network formalization of predictive processing can explain this process.
Quantitative and qualitative evaluation of the impact of the G2 enhancer, bead sizes and lysing tubes on the bacterial community composition during DNA extraction from recalcitrant soil core samples based on community sequencing and qPCR
Authors: Gobbi Alex , Santini Rui G. , Filippi Elisa , Jensen Lea Ellegaard- , Jacobsen Carsten S. , Hansen Lars H. 
Published: July 2018

AbstractSoil DNA extraction encounters numerous challenges that can affect both yield and purity of the recovered DNA. Clay particles lead to reduced DNA extraction efficiency, and PCR inhibitors from the soil matrix can negatively affect downstream analyses when applying DNA sequencing. Further, these effects impede molecular analysis of bacterial community compositions in lower biomass samples, as often observed in deeper soil layers. Many studies avoid these complications by using indirect DNA extraction with prior separation of the cells from the matrix, but such methods introduce other biases that influence the resulting microbial community composition.To address these issues, a direct DNA extraction method was applied in combination with the use of a commercial product, the G2 DNA/RNA Enhancer®, marketed as being capable of improving the amount of DNA recovered after the lysis step. The results showed that application of G2 increased DNA yields from the studied clayey soils from layers between 1.00 and 2.20 m below ground level.Importantly, the use of G2 did not introduce bias, as it did not result in any significant differences in the biodiversity of the bacterial community measured in terms of alpha and beta diversity and taxonomical composition.Finally, this study considered a set of customised lysing tubes for evaluating possible influences on the DNA yield. Tubes customization included different bead sizes and amounts, along with lysing tubes coming from two suppliers. Results showed that the lysing tubes with mixed beads allowed greater DNA recovery compared to the use of either 0.1 or 1.4 mm beads, irrespective of the tube supplier.These outcomes may help to improve commercial products in DNA/RNA extraction kits, besides raising awareness about the optimal choice of additives, offering opportunities for acquiring a better understanding of topics such as vertical microbial characterisation and environmental DNA recovery in low biomass samples.
Single-cell transcriptomics characterizes cell types in the subventricular zone and uncovers molecular defects underlying impaired adult neurogenesis
Authors: Zywitza Vera , Misios Aristotelis , Bunatyan Lena , Willnow Thomas E. , Rajewsky Nikolaus 
Published: July 2018

SUMMARYNeural stem cells (NSCs) contribute to plasticity and repair of the adult brain. Niches harboring NSCs are crucial for regulating stem cell self-renewal and differentiation. We used single-cell RNA profiling to generate an unbiased molecular atlas of all cell types in the largest neurogenic niche of the adult mouse brain, the subventricular zone (SVZ). We characterized > 20 neural and non-neural cell types and gained insights into the dynamics of neurogenesis by predicting future cell states based on computational analysis of RNA kinetics. Furthermore, we apply our single-cell approach to mice lacking LRP2, an endocytic receptor required for SVZ maintenance. The number of NSCs and proliferating progenitors was significantly reduced. Moreover, Wnt and BMP4 signaling was perturbed. We provide a valuable resource for adult neurogenesis, insights into SVZ neurogenesis regulation by LRP2, and a proof-of-principle demonstrating the power of single-cell RNA-seq in pinpointing neural cell type-specific functions in loss-of-function models.HIGHLIGHTSunbiased single-cell transcriptomics characterizes adult NSCs and their nichecell type-specific signatures and marker genes for 22 SVZ cell typesFree online tool to assess gene expression across 9,804 single cellscell type-specific dysfunctions underlying impaired adult neurogenesis