bluuebunny/crossref_metadata_2025_split huggingface dataset:
Feasibility analysis of semiconductor voltage nanosensors for neuronal membrane potential sensing
Authors: Ludwig Anastasia , Serna Pablo , Morgenstein Lion , Yang Gaoling , Bar-Elli Omri , Ortiz Gloria , Miller Evan , Oron Dan , Grupi Asaf , Weiss Shimon , Triller Antoine 
Published: November 2019

AbstractIn the last decade, optical imaging methods have significantly improved our understanding of the information processing principles in the brain. Although many promising tools have been designed, sensors of membrane potential are lagging behind the rest. Semiconductor nanoparticles are an attractive alternative to classical voltage indicators, such as voltage-sensitive dyes and proteins. Such nanoparticles exhibit high sensitivity to external electric fields via the quantum-confined Stark effect. Here we report the development of lipid-coated semiconductor voltage-sensitive nanorods (vsNRs) that self-insert into the neuronal membrane. We describe a workflow to detect and process the photoluminescent signal of vsNRs after wide-field time-lapse recordings. We also present data indicating that vsNRs are feasible for sensing membrane potential in neurons at a single-particle level. This shows the potential of vsNRs for detection of neuronal activity with unprecedentedly high spatial and temporal resolution.
Long-term warming effects on the microbiome and nitrogen fixation of a common moss species in sub-Arctic tundra
Authors: Klarenberg Ingeborg J. , Keuschnig Christoph , Colmenares Ana J. Russi , Warshan Denis , Jungblut Anne D. , Jónsdóttir Ingibjörg S. , Vilhelmsson Oddur 
Published: November 2019

AbstractBacterial communities form the basis of biogeochemical processes and determine plant growth and health. Mosses, an abundant plant group in Arctic ecosystems, harbour diverse bacterial communities that are involved in nitrogen fixation and carbon cycling. Global climate change is causing changes in aboveground plant biomass and shifting species composition in the Arctic, but little is known about the response of moss microbiomes.Here, we studied the total and potentially active bacterial community associated withRacomitrium lanuginosum, in response to 20-yearin situwarming in an Icelandic heathland. We evaluated the effect of warming and warming-induced shrub expansion on the moss bacterial community composition and diversity,nifHgene abundance and nitrogen-fixation rates.Warming changed both the total and the potentially active bacterial community structure, while litter abundance only affected the total bacterial community structure. The relative abundance of Proteobacteria increased, while the relative abundance of Cyanobacteria and Acidobacteria decreased.NifHgene abundance and nitrogen-fixation rates were negatively affected by litter andBetula nanaabundance, respectively. We also found shifts in the potentially nitrogen-fixing community, withNostocdecreasing and non-cyanobacterial diazotrophs increasing in relative abundance. Our data suggests that the moss microbial community including the potentially nitrogen-fixing taxa is sensitive to future warming.Synthesis.Long-term warming led to a shift in moss-associated bacterial community composition, while the abundance of nitrogen-fixing bacteria and nitrogen-fixation rates were negatively affected by increased litter andBetula nanaabundance respectively. Warming and increased shrub abundance as a result of warming can affect moss-associated bacterial communities and nitrogen fixation rates in tundra ecosystems.
Robust Moiety Model Selection Using Mass Spectrometry Measured Isotopologues
Authors: Jin Huan , Moseley Hunter N.B. 
Published: November 2019

AbstractStable isotope resolved metabolomics (SIRM) experiments uses stable isotope tracers to provide superior mass spectroscopy (MS) and nuclear magnetic resonance (NMR) metabolomics datasets for metabolic flux analysis and metabolic modeling. Several software packages exist for metabolic flux analysis when provided a metabolic model and appropriate isotopomer and/or isotopologue datasets, mostly from 13C tracer time series experiments. However, assumptions of model correctness can seriously compromise interpretation of metabolic flux results generated from these packages. Therefore, we have developed a metabolic modeling software package specifically designed for moiety model comparison and selection based on the metabolomics data provided. This moiety modeling framework facilitates analysis of time-series SIRM MS isotopologue profiles using a set of plausible moiety models and data in a JSONized representation. The moiety_modeling Python package is available on GitHub and the Python Package Index and provides facilities for model parameter optimization, analysis of optimization results, and model selection. Furthermore, this package is capable of analyzing multi-tracer datasets. Here, we tested the effectiveness of this moiety modeling framework in model selection with two sets of time-series MS isotopologue datasets for uridine diphosphate N-acetyl-D-glucosamine (UDP-GlcNAc) generated from different MS platforms: direct infusion nanoelectrospray Fourier transform MS and liquid chromatography MS. Results generated from the analyses of these datasets demonstrate the robustness of our model selection methods by the successful selection of the optimal model from over 40 models provided. Also, the effects of specific optimization methods, degree of optimization, selection criteria, and specific objective functions on model selection are illustrated. Furthermore, different types of error can exist in the datasets, and proper selection of the objective function can help reduce the optimization side effects caused by the specific types of uncertainty in these datasets. Overall, these results indicate that over-optimization can lead to failure in model selection, but combining multiple datasets can help prevent this overfitting effect. The implication is that SIRM datasets in public repositories of reasonable quality can be combined with newly acquired datasets to improve model selection. Furthermore, curation efforts of public metabolomics repositories to maintain high data quality could have huge impacts on future metabolic modeling efforts.
Defining Essential Enhancer for Pluripotent stem cells using Features Oriented CRISPR-Cas9 Screen
Authors: Wang Hao Fei , Warrier Tushar , Farran Chadi EL , Zihao Zheng , Xing Qiao Rui , Fullwood Melissa J , Zhang Li-Feng , Li Hu , Xu Jian , Lim Tit-Meng , Loh Yuin-Han 
Published: November 2019

ABSTRACTCis Regulatory Elements (CREs) regulate the expression of the genes in their genomic neighborhoods and influence cellular processes such as cell-fate maintenance and differentiation. To date, there remain major gaps in the functional characterization of CREs and the identification of its target genes in the cellular native environment. In this study, we performed a Features Oriented CRISPR Utilized Systematic (FOCUS) screen of OCT4-bound CREs using CRISPR/Cas9 to identify functional enhancers important for pluripotency maintenance in mouse ES cells. From the initial 235 candidates tested, 16 CREs were identified to be essential stem cell enhancers. Using RNA-seq and genomic 4C-seq, we further uncovered a complex network of candidate CREs and their downstream target genes, which supports the growth and self-renewal of mESCs. Notably, an essential enhancer, CRE111, and its target, Lrrc31, form the important switch to modulate the LIF-JAK1-STAT3 signaling pathway.
Characterization of GRK5 as a novel regulator of rhabdomyosarcoma tumor cell growth and self-renewal
Authors: Pham Thao , Robinson Kristin , Vleeshouwer-Neumann Terra , Annis James E. , Chen Eleanor Y. 
Published: November 2019

AbstractRhabdomyosarcoma (RMS) is the most common soft-tissue pediatric sarcoma. Treatment options remain limited, presenting an urgent need for novel therapeutic targets. Using a high-throughput siRNA screen against the human kinome, we identified GRK5, a G-protein receptor kinase, as a novel regulator of RMS tumor cell growth and self-renewal. Through functional assays in vitro and in vivo, we show that GRK5 regulates cell cycling in a kinase-independent manner to promote RMS tumor cell growth. GRK5 interacts with NFAT to facilitate autoregulation of NFAT1 expression in a kinase independent manner, and loss of NFAT1 phenocopies GRK5 loss-of-function effects on cell cycle arrest. Self-renewal of RMS, required for recapitulation of tumor heterogeneity, is significantly reduced with loss of GRK5 due to increased cell death. Treatment of human RMS xenografts in mice with CCG-215022, a GRK5-selective inhibitor, reduces tumor growth of RMS. GRK5 represents a novel therapeutic target for the treatment of RMS.Statement of SignificanceGRK5 promotes growth and self-renewal of RMS, thereby representing a novel therapeutic target for improving survival outcomes of RMS patients. GRK5 regulates RMS tumor cell growth in a kinase-independent manner through direct interaction with NFAT1. This finding promises novel drug design, targeting non-kinase domains of GRK5.
OpenSim Moco: Musculoskeletal optimal control
Authors: Dembia Christopher L. , Bianco Nicholas A. , Falisse Antoine , Hicks Jennifer L. , Delp Scott L. 
Published: November 2019

AbstractMusculoskeletal simulations of movement can provide insights needed to help humans regain mobility after injuries and design robots that interact with humans. Here, we introduce Open-Sim Moco, a software toolkit for optimizing the motion and control of musculoskeletal models built in the OpenSim modeling and simulation package. OpenSim Moco uses the direct collocation method, which is often faster and can handle more diverse problems than other methods for musculoskeletal simulation but requires extensive technical expertise to implement. Moco frees researchers from implementing direct collocation themselves, allowing them to focus on their scientific questions. The software can handle the wide range of problems that interest biomechanists, including motion tracking, motion prediction, parameter optimization, model fitting, electromyography-driven simulation, and device design. Moco is the first musculoskeletal direct collocation tool to handle kinematic constraints, which are common in musculoskeletal models. To show Moco’s abilities, we first solve for muscle activity that produces an observed walking motion while minimizing muscle excitations and knee joint loading. Then, we predict a squat-to-stand motion and optimize the stiffness of a passive assistive knee device. We designed Moco to be easy to use, customizable, and extensible, thereby accelerating the use of simulations to understand human and animal movement.
Spatiotemporal dynamics and modelling support the case for area-wide management of citrus greasy spot in a Brazilian smallholder farming region
Authors: Laranjeira F.F. , Silva S.X.B. , Murray-Watson R.E. , Soares A.C.F. , Santos-Filho H.P. , Cunniffe N.J. 
Published: November 2019

AbstractCitrus greasy spot (CGS), caused byZasmidium citri, induces premature defoliation and yield loss inCitrusspp. CGS epidemiology is well understood in areas of high humidity such as Florida (USA), but remains unaddressed in Brazil, despite differing climatic conditions and disease management practices. We characterize the spatiotemporal dynamics of CGS in the Recôncavo of Bahia, Brazil, focusing on four hierarchical levels (quadrant, plant, grove and region). A survey conducted in 19 municipalities showed that disease is found throughout the entire region with a prevalence (i.e. proportion of affected sampling units) of 100% in groves and plants, and never lower than 70% on leaves. Index of dispersion (D) values suggest the spatial pattern of symptomatic units lies somewhere between random and regular. This was confirmed by the parameters of the binary power law for plants and their quadrants (log(A)<0 andb<1). Variability in disease severity at different plant heights (0.7 m, 1.3 m and 2.0 m) was tested, but no consistent differences were observed. We introduce a simple compartmental model synthesising the epidemiology of the disease, in order to motivate and guide further research. The data we have collected allow such a model to be parameterised, albeit with some ambiguity over the proportion of new infections that result from inoculum produced within the grovevs.external sources of infection. By extending our model to include two populations of growers – those who control and those who do not – coupled by the spread of airborne inoculum, we investigate likely performance of the type of cultural controls that would be accessible to citrus growers in Northeastern Brazil. Our model shows that control via removal of the key source of inoculum – i.e. fallen leaves – can be very effective. However, successful control is likely to require area-wide strategies, in which a large proportion of growers actively manage disease.
Cross-modal temporal biases emerge during early sensitive periods
Authors: Badde Stephanie , Ley Pia , Rajendran Siddhart S , Shareef Idris , Kekunnaya Ramesh , Röder Brigitte 
Published: November 2019

AbstractHuman perception features stable biases, such as perceiving visual events as later than synchronous auditory events. The origin of such perceptual biases is unknown, they could be innate or shaped by sensory experience during a sensitive period. To investigate the role of sensory experience, we tested whether a congenital, transient loss of vision, caused by bilateral dense cataracts, has sustained effects on the ability to order events spatio-temporally within and across sensory modalities. Most strikingly, individuals with reversed congenital cataracts showed a bias towards perceiving visual stimuli as occurring earlier than auditory (Exp. 1) and tactile (Exp. 2) stimuli. In contrast, both normally sighted controls and individuals who could see at birth but developed cataracts during childhood reported the typical bias of perceiving vision as delayed compared to audition. Thus, we provide strong evidence that cross-modal temporal perceptual biases depend on sensory experience and emerge during an early sensitive period.
Lysyl oxidase promotes neuronal ferroptosis exacerbating seizure-induced hippocampal damage
Authors: Mao Xiao-Yuan , Jin Ming-Zhu , Li Qin , Jia Ji-Ning , Sun Qian-Yi , Zhou Hong-Hao , Liu Zhao-Qian , Jin Wei-Lin 
Published: November 2019

AbstractEpilepsy is a serious neurological disorder and characterized by recurrent and unprovoked seizures. A critical pathological factor in the seizure genesis is neuronal loss. However, mechanisms which lead to neuronal death remain elusive. Our present investigation depicted that ferroptosis, a recently discovered iron- and lipid peroxidation-dependent cell death, probably served as a mechanism in murine models of kainic acid (KA)-induced seizures. And treatment with ferroptosis inhibitors ferrostatin-1 (Fer-1), liproxstatin-1 (Lipo-1) or deferoxamine (DFO) significantly suppressed seizure severity and frequency. Using gene expression profiling in HT22 cells after glutamate exposure (a validated ferroptotic cell death model), we identified lysyl oxidase (Lox) as a novel inducer of ferroptosis. Mechanistically, Lox promoted ferroptosis via activation of extracellular regulated protein kinase (ERK)-dependent 5-lipoxygenase (Alox5) phosphorylation at serine 663 residue signaling, subsequent leading to lipid reactive oxygen species (ROS) accumulation. In a murine model of KA-induced seizure, we illustrated that administration of β-aminopropionitrile (BAPN), a specific Lox inhibitor, remarkably prevented seizure generation. Overall, these findings highlight Lox, a novel identified ferroptotic regulator in neurons, serves as a potential target for seizure-related disease including epilepsy.
Effect of arbuscular mycorrhizal fungi (AMF) and plant growth promoting rhizobacteria (PGPR) on microbial community structure of phenanthrene and pyrene contaminated soils using Illumina HiSeq sequencing
Authors: Li Wen-bin , Li Wei , Xing Li-jun , Guo Shao-xia 
Published: November 2019

AbstractIn order to determine the influence of arbuscular mycorrhizal fungi (AMF, Glomus versiforme) and plant growth promoting rhizobacteria (PGPR, Pseudomonas fluorescens, PS2-6) on degradation of phenanthrene (PHE) and pyrene (PYR) and the change of microbial community structure in soils planted with tall fescue (Festuca elata), four treatments were set up in phenanthrene (PHE) and pyrene (PYR) contamined soil: i.e., tall fescue (CK), AMF + tall fescue (GV), PGPR + tall fescue (PS) and AMF + PGPR + tall fescue (GVPS), PHE and PYR dissipation in the soil and accumulated in the tall fescue were investigated. Our results showed that highest removal percentage of PHE and PYR in contaminated soil as well as biomass of tall fescue were observed in GVPS. PHE and PYR accumulation by tall fescue roots were higher than shoots, the mycorrhizal status was best manifested in the roots of tall fescue inoculated with GVPS, and GVPS significantly increased the number of PGPR colonization in tall fescue rhizosphere soil. And paired-end Illumina HiSeq analysis of 16S rRNA and Internal Transcribed Spacer (ITS) gene amplicons were also employed to study change of bacterial and fungal communities structure in four treatments. GVPS positively affected the speices and abundance of bacteria and fungi in PHE and PYR contaminated soil, an average of 71,144 high quality bacterial 16S rDNA tags and 102,455 ITS tags were obtained in GVPS, and all of them were assigned to 6,327 and 825 operational taxonomic units (OTUs) at a 97% similarity, respectively. Sequence analysis revealed that Proteobacteria was the dominant bacterial phylum, Ascomycota was the dominant fungal phylum in all treatments, whereas Proteobacteria and Glomeromycota were the most prevalent bacterial and fungal phyla in GVPS, respectively. And in the generic level, Planctomyces is the richest bacterial genus, and Meyerozyma is the richest fungal genus in all treatments, whereas Sphingomona was the dominant bacterial genus, while the dominant fungi was Fusarium in GVPS. Overall, our findings revealed that application of AMF and PGPR had an effective role in improving the growth characteristics, root colonization of F. elata and soil microbial community structure in PHE and PYR contaminated soils, but no obvious in degradation efficiencies of PAHs as compared to the control.
Live Cell Imaging of Single RNA Molecules with Fluorogenic Mango II Arrays
Authors: Cawte Adam D. , Unrau Peter J. , Rueda David S. 
Published: November 2019

AbstractRNA molecules play vital roles in many cellular processes. Visualising their dynamics in live cells at single-molecule resolution is essential to elucidate their role in RNA metabolism. RNA aptamers, such as Spinach and Mango, have recently emerged as a powerful background-free technology for live-cell RNA imaging due to their fluorogenic properties upon ligand binding. Here, we report a novel array of Mango II aptamers for RNA imaging in live and fixed cells with high contrast and single-molecule sensitivity. Direct comparison of Mango II and MS2-tdMCP-mCherry dual-labelled mRNAs show marked improvements in signal to noise ratio using the fluorogenic Mango aptamers. Using both coding (β-actin mRNA) and long non-coding (NEAT1) RNAs, we show that the Mango array does not affect cellular localisation. Additionally, we can track single mRNAs for extended time periods, likely due to fluorophore exchange. This property makes the arrays readily compatible with structured illumination super-resolution microscopy.
Pre-Innervated Tissue Engineered Muscle Promotes a Pro-Regenerative Microenvironment Following Volumetric Muscle Loss
Authors: Das Suradip , Browne Kevin D. , Laimo Franco A. , Maggiore Joseph C. , Kaisaier Halimulati , Aguilar Carlos A. , Ali Zarina S. , Mourkioti Foteini , Cullen D. Kacy 
Published: November 2019

AbstractVolumetric Muscle Loss (VML) is defined as traumatic or surgical loss of skeletal muscle tissue beyond the inherent regenerative capacity of the body, generally leading to a severe functional deficit. Autologous muscle grafts remain the prevalent method of treatment whereas recent muscle repair techniques using biomaterials and tissue engineering are still at a nascent stage and have multiple challenges to address to ensure functional recovery of the injured muscle. Indeed, appropriate somato-motor innervations remain one of the biggest challenges for both autologous muscle grafts as well as tissue engineered muscle constructs. We aim to address this challenge by developing Pre-Innervated Tissue Engineered Muscle comprised of long aligned networks of spinal motor neurons and skeletal myocytes. Here, we developed methodology to biofabricate long fibrils of pre-innervated tissue engineered muscle using a co-culture of myocytes and motor neurons on aligned nanofibrous scaffolds. Motor neurons lead to enhanced differentiation and maturation of skeletal myocytes in vitro. These pre-innervated tissue engineered muscle constructs when implanted in vivo in a rat VML model significantly increase satellite cell migration, micro-vessel formation, and neuromuscular junction density in the host muscle near the injury area at an acute time point as compared to non-pre-innervated myocyte constructs and nanofiber scaffolds alone. These pro-regenerative effects can potentially lead to enhanced functional neuromuscular regeneration following VML, thereby improving the levels of functional recovery following these devastating injuries.
A demographic approach to understanding the effects of climate on population growth
Authors: Caruso Nicholas M. , Staudhammer Christina L. , Rissler Leslie J. 
Published: November 2019

AbstractAmphibian life history traits are affected by temperature and precipitation. Yet, connecting these relationships to population growth, especially for multiple populations within a species, is lacking and precludes our understanding of how amphibians are distributed. Therefore, we constructed Integral Projection Models (IPM) for five populations along an elevational gradient to determine how climate and season affects population growth of a terrestrial salamanderPlethodon montanusand the importance of demographic vital rates to population growth under varying climate scenarios. We found that population growth was typically higher at the highest elevation compared to the lower elevations whereas varying inactive season conditions, represented by the late fall, winter and early spring, produced a greater variation in population growth than varying active season conditions (late spring, summer, and early fall). Furthermore, survival and growth was consistently more important, as measured by elasticity, compared to fecundity and large females had the greatest elasticity compared to all other sizes. Our results suggest that changing inactive season conditions, especially those that would affect the survival of large individuals, may have the greatest impact on population growth. Therefore, we recommend experimental studies focused on the inactive season to determine the mechanism by which these conditions can affect survival.