bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alpha oscillations and travelling waves: signatures of predictive coding?
Authors: Alamia Andrea , VanRullen Rufin 
Published: November 2018

AbstractPredictive coding is a key mechanism to understand the computational processes underlying brain functioning: in a hierarchical network, higher layers predict the activity of lower layers, and the unexplained residuals (i.e. prediction errors) are sent through. Because of its iterative nature, we wondered whether predictive coding could be related to brain oscillatory dynamics. First, we show that a simple 2-layers predictive coding model of visual cortex, with physiological communication delays between layers, naturally gives rise to alpha-band rhythms, similar to experimental observations. Then, we demonstrate that a multi-layer version of the same model can explain the occurrence of oscillatory travelling waves across layers, both feedforward (during visual stimulation) and backward (during rest). Remarkably, the predictions of our model are matched by the analysis of two independent EEG datasets, in which we observed oscillatory travelling waves in both directions.
Mechanism and resistance for antimycobacterial activity of a fluoroquinophenoxazine compound
Authors: Garcia Pamela K. , Annamalai Thirunavukkarasu , Wang Wenjie , Bell Raven , Le Duc , Pancorbo Paula Martin , Sikandar Sabah , Seddek Ahmed , Yu Xufen , Sun Dianqing , Uhlemann Anne-Catrin , Tiwari Purushottam B. , Leng Fenfei , Tse-Dinh Yuk-Ching 
Published: November 2018

AbstractWe have previously reported the inhibition of bacterial topoisomerase I activity by a fluoroquinophenoxazine compound (FP-11g) with a 6-bipiperidinyl lipophilic side chain that exhibited promising antituberculosis activity (MIC = 2.5 μM againstMycobacterium tuberculosis, SI = 9.8). Here, we found that the compound is bactericidal towardsMycobacterium smegmatis, resulting in greater than 5 Log10reduction in colony-forming units [cfu]/mL following a 10 h incubation at 1.25 μM (4X MIC) concentration. Growth inhibition (MIC = 50 μM) and reduction in cfu could also be observed against a clinical isolate ofMycobacterium abscessus.Stepwise isolation of resistant mutants ofM. smegmatiswas conducted to explore the mechanism of resistance. Mutations in the resistant isolates were identified by direct comparison of whole-genome sequencing data from mutant and wild-type isolates. These include mutations in genes likely to affect the entry and retention of the compound. FP-11g inhibitsMtbtopoisomerase I andMtbgyrase with IC50of 0.24 and 31.5 μM, respectively. Biophysical analysis showed that FP-11g binds DNA as an intercalator but the IC50for inhibition ofMtbtopoisomerase I activity is >10 fold lower than the compound concentrations required for producing negatively supercoiled DNA during ligation of nicked circular DNA. Thus, the DNA-binding property of FP-11g may contribute to its antimycobacterial mechanism, but that alone cannot account for the observed inhibition of Mtb topoisomerase I.
High-throughput micro-patterning platform reveals Nodal-dependent dissection of peri-gastrulation-associated versus pre-neurulation associated fate patterning
Authors: Tewary Mukul , Dziedzicka Dominika , Ostblom Joel , Prochazka Laura , Shakiba Nika , Woodford Curtis , Piccinini Elia , Vickers Alice , Louis Blaise , Rahman Nafees , Danovi Davide , Geens Mieke , Watt Fiona M. , Zandstra Peter W. 
Published: November 2018

AbstractIn vitromodels of post-implantation human development are valuable to the fields of regenerative medicine and developmental biology. Here, we report characterization of a robustin vitroplatform that enabled high-content screening of multiple human pluripotent stem cell (hPSC) lines for their ability to undergo peri-gastrulation-like fate patterning upon BMP4 treatment of geometrically-confined colonies and observed significant heterogeneity in their differentiation propensities along a gastrulation associable and neuralization associable axis. This cell line associated heterogeneity was found to be attributable to endogenous nodal expression, with upregulation of Nodal correlated with expression of a gastrulation-associated gene profile, and Nodal downregulation correlated with a neurulation-associated gene profile expression. We harness this knowledge to establish a platform of pre-neurulation-like fate patterning in geometrically confined hPSC colonies that arises due to a stepwise activation of reaction-diffusion and positional-information. Our work identifies a Nodal signalling dependent switch in peri-gastrulation versus pre-neurulation-associated fate patterning in hPSC cells, provides a technology to robustly assay hPSC differentiation outcomes, and suggests conserved mechanisms of self-organized fate specification in differentiating epiblast and ectodermal tissues.
A dynamic network model can explain temporal receptive fields in primary auditory cortex
Authors: Rahman Monzilur , Willmore Ben D. B. , King Andrew J. , Harper Nicol S. 
Published: November 2018

ABSTRACTAuditory neurons encode stimulus history, which is often modelled using a span of time-delays in a spectro-temporal receptive field (STRF). We propose an alternative model for the encoding of stimulus history, which we apply to extracellular recordings of neurons in the primary auditory cortex of anaesthetized ferrets. For a linear-non-linear STRF model (LN model) to achieve a high level of performance in predicting single unit neural responses to natural sounds in the primary auditory cortex, we found that it is necessary to include time delays going back at least 200 ms in the past. This is an unrealistic time span for biological delay lines. We therefore asked how much of this dependence on stimulus history can instead be explained by dynamical aspects of neurons. We constructed a neural-network model whose output is the weighted sum of units whose responses are determined by a dynamic firing-rate equation. The dynamic aspect performs low-pass filtering on each unit’s response, providing an exponentially decaying memory whose time constant is individual to each unit. We find that this dynamic network (DNet) model, when fitted to the neural data using STRFs of only 25 ms duration, can achieve prediction performance on a held-out dataset comparable to the best performing LN model with STRFs of 200 ms duration. These findings suggest that integration due to the membrane time constants or other exponentially-decaying memory processes may underlie linear temporal receptive fields of neurons beyond 25 ms.AUTHOR SUMMARYThe responses of neurons in the primary auditory cortex depend on the recent history of sounds over seconds or less. Typically, this dependence on the past has been modelled by applying a wide span of time delays to the input, although this is likely to be biologically unrealistic. Real neurons integrate the history of their activity due to the dynamical properties of their cell membranes and other components. We show that a network with a realistically narrow span of delays and with units having dynamic characteristics like those found in neurons, succinctly models neural responses recorded from ferret primary auditory cortex. Because these integrative properties are widespread, our dynamic network provides a basis for modelling responses in other neural systems.
The NDV-3A vaccine protects mice from multidrug resistantCandida aurisinfection
Authors: Singh Shakti , Uppuluri Priya , Alqarihi Abdullah , Elhassan Hana , French Samuel , Lockhart Shawn R. , Chiller Tom , Edwards John E. , Ibrahim Ashraf S. 
Published: November 2018

AbstractCandida aurisis an emerging, multi-drug resistant, health care-associated fungal pathogen. Its predominant prevalence in hospitals and nursing homes indicates its ability to adhere to and colonize the skin, or persist in an environment outside the host - a trait unique from otherCandidaspecies. Besides being associated globally with life-threatening disseminated infections,C. aurisalso poses significant clinical challenges due to its ability to adhere to polymeric surfaces and form highly drug-resistant biofilms. Here, we performed bioinformatic studies to identify the presence of adhesin proteins inC. auris, with sequence as well as 3-D structural homologies to the major adhesin/invasin ofC. albicans, Als3. Anti-Als3p antibodies generated by vaccinating mice with NDV-3A (a vaccine based on the N-terminus of Als3 protein formulated with alum) recognizedC. auris in vitro, blocked its ability to form biofilms and enhanced macrophage-mediated killing of the fungus. Furthermore, NDV-3A vaccination induced significant levels ofC. auriscross-reactive humoral and cellular immune responses, and protected immunosuppressed mice from lethalC. aurisdisseminated infection, compared to the control alum-vaccinated mice. Finally, NDV-3A potentiated the protective efficacy of the antifungal drug micafungin, againstC. auriscandidemia. Identification of Als3-like adhesins inC. aurismakes it a target for immunotherapeutic strategies using NDV-3A, a vaccine with known efficacy against otherCandidaspecies and safety as well as efficacy in clinical trials. Considering thatC. auriscan be resistant to almost all classes of antifungal drugs, such an approach has profound clinical relevance.Author SummaryCandida aurishas emerged as a major health concern to hospitalized patients and nursing home subjects.C. aurisstrains display multidrug resistance to current antifungal therapy and cause lethal infections. We have determined thatC. aurisharbors homologs ofC. albicansAls cell surface proteins. TheC. albicansNDV-3A vaccine, harboring the N-terminus of Als3p formulated with alum, generates cross-reactive antibodies againstC. aurisclinical isolates and protects neutropenic mice from hematogenously disseminatedC. aurisinfection. Importantly, the NDV-3A vaccine displays an additive protective effect in neutropenic mice when combined with micafungin. Due to its proven safety and efficacy in humans againstC. albicansinfection, our studies support the expedited testing of the NDV-3A vaccine againstC. aurisin future clinical trials.
Plastic multicellular development ofMyxococcus xanthus: genotype-environment interactions in a physical gradient
Authors: Rivera-Yoshida Natsuko , Arzola Alejandro V. , Arias Del Angel Juan A. , Franci Alessio , Travisano Michael , Escalante Ana E. , Benítez Mariana 
Published: November 2018

AbstractIn order to investigate the contribution of the physical environment to variation in multicellular development ofMyxococcus xanthus, phenotypes developed by different genotypes in a gradient of substrate stiffness conditions were quantitatively characterized. Statistical analysis showed that plastic phenotypes result from the genotype, the substrate conditions and the interaction between them. Also, phenotypes were expressed with scale- and trait-specificity. Overall, the presented information highlights the constructive role of the physical context in the development of microbial multicellularity, with both ecological and evolutionary implications.
duphold: scalalable, depth-based annotation and curation of high-confidence structural variant calls
Authors: Pedersen Brent S. , Quinlan Aaron R. 
Published: November 2018

AbstractMost structural variant detection tools use clusters of discordant read-pair and split-read alignments to identify variants, yet do not integrate depth of sequence coverage as an additional means to support or refute putative events. Here, we present duphold, as a new method to efficiently annotate structural variant calls with sequence depth information that can add (or remove) confidence to SV predicted to affect copy number. It indicates not only the change in depth across the event, but also the presence of a rapid change in depth relative to the regions surrounding the breakpoints. It uses a unique algorithm that allows the run time to be nearly independent of the number of variants. This performance is important for large, jointly-called projects with many samples, each of which must be evaluated at thousands of sites. We show that filtering on duphold annotations can greatly improve the specificity of deletion calls and that its annotations match visual inspection. Duphold can annotate structural variant predictions made from both short-read and long-read data. It is available under the MIT license at: https://github.com/brentp/duphold.
Bayesian computation through cortical latent dynamics
Authors: Sohn Hansem , Narain Devika , Meirhaeghe Nicolas , Jazayeri Mehrdad 
Published: November 2018

AbstractStatistical regularities in the environment create prior beliefs that we rely on to optimize our behavior when sensory information is uncertain. Bayesian theory formalizes how prior beliefs can be leveraged, and has had a major impact on models of perception 1, sensorimotor function 2,3, and cognition 4. However, it is not known how recurrent interactions among neurons mediate Bayesian integration. Using a time interval reproduction task in monkeys, we found that prior statistics warp the underlying structure of population activity in the frontal cortex allowing the mapping of sensory inputs to motor outputs to be biased in accordance with Bayesian inference. Analysis of neural network models performing the task revealed that this warping was mediated by a low-dimensional curved manifold, and allowed us to further probe the potential causal underpinnings of this computational strategy. These results uncover a simple and general principle whereby prior beliefs exert their influence on behavior by sculpting cortical latent dynamics.
Distance-based Protein Folding Powered by Deep Learning
Authors: Xu Jinbo 
Published: November 2018

AbstractDirect coupling analysis (DCA) for protein folding has made very good progress, but it is not effective for proteins that lack many sequence homologs, even coupled with time-consuming folding simulation. We show that we can accurately predict the distance matrix of a protein by deep learning, even for proteins with ∼60 sequence homologs. Using only the geometric constraints given by the resulting distance matrix we may construct 3D models without involving any folding simulation. Our method successfully folded 21 of the 37 CASP12 hard targets with a median family size of 58 effective sequence homologs within 4 hours on a Linux computer of 20 CPUs. In contrast, DCA cannot fold any of these hard targets in the absence of folding simulation, and the best CASP12 group folded only 11 of them by integrating DCA-predicted contacts into complex, fragment-based folding simulation. Rigorous experimental validation in CASP13 shows that our distance-based folding server successfully folded 17 of 32 hard targets (with a median family size of 36 sequence homologs) and obtained 70% precision on top L/5 long-range predicted contacts. Latest experimental validation in CAMEO shows that our server predicted correct fold for two membrane proteins of new fold while all the other servers failed. These results imply that it is now feasible to predict correct fold for proteins lack of similar structures in PDB on a personal computer without folding simulation.SignificanceAccurate description of protein structure and function is a fundamental step towards understanding biological life and highly relevant in the development of therapeutics. Although greatly improved, experimental protein structure determination is still low-throughput and costly, especially for membrane proteins. As such, computational structure prediction is often resorted. Predicting the structure of a protein with a new fold (i.e., without similar structures in PDB) is very challenging and usually needs a large amount of computing power. This paper shows that by using a powerful deep learning technique, even with only a personal computer we can predict new folds much more accurately than ever before. This method also works well on membrane protein folding.
Viable and efficient electroporation-based genetic manipulation of unstimulated human T cells
Authors: Aksoy Pinar , Aksoy Bülent Arman , Czech Eric , Hammerbacher Jeff 
Published: November 2018

AbstractElectroporation is the most feasible non-viral material delivery system for manipulating human T cells given its time- and cost-effectiveness. However, efficient delivery requires electroporation settings to be optimized for different devices, cellular states, and materials to be delivered. Here, we used electroporation to either induce exogenous gene expression in human primary T cells by plasmids or in vitro transcribed (IVT) mRNA and also target endogenous genes by Cas9 ribonucleoproteins (RNPs). We characterized the electroporation conditions both for activated and unstimulated human T cells. Although naive cells are non-dividing and therefore their genetic manipulation is harder compared to activated T cells, we developed the technical ability to manipulate both naive and memory cells within the unstimulated T cell population by IVT mRNA and Cas9 RNP electroporation. Here, we outline the best practices for achieving highly-efficient genetic manipulation in primary T cells without causing significant cytotoxicity to the cells. Because there is increasing evidence for “less-differentiated” T cells to have better anti-tumor activity for immunotherapy, manipulating naive T cells with high efficiency is also of high importance to clinical applications and to study the biology of these cells.
Early detonation by sprouted mossy fibers enables aberrant dentate network activity
Authors: Hendricks William D. , Westbrook Gary L. , Schnell Eric 
Published: November 2018

AbstractIn temporal lobe epilepsy, sprouting of hippocampal mossy fiber axons onto dentate granule cell dendrites creates a recurrent excitatory network. However, unlike mossy fibers projecting to CA3, sprouted mossy fiber synapses depress upon repetitive activation. Thus, despite their proximal location, large presynaptic terminals, and ability to excite target neurons, the impact of sprouted mossy fiber synapses on hippocampal hyperexcitability is unclear. We find that despite their short-term depression, single episodes of sprouted mossy fiber activation in hippocampal slices initiated bursts of recurrent polysynaptic excitation. Consistent with a contribution to network hyperexcitability, optogenetic activation of sprouted mossy fibers reliably triggered action potential firing in postsynaptic dentate granule cells after single light pulses. This pattern resulted in a shift in network recruitment dynamics to an “early detonation” mode and an increased probability of release compared to mossy fiber synapses in CA3. A lack of tonic adenosine-mediated inhibition contributed to the higher probability of glutamate release thus facilitating reverberant circuit activity.Significance StatementSprouted mossy fibers are one of the hallmark histopathological findings in temporal lobe epilepsy. These fibers form recurrent excitatory synapses onto other dentate granule cells that display profound short-term depression. Here, however, we show that although these sprouted mossy fibers weaken substantially during repetitive activation, their initial high probability of glutamate release can activate reverberant network activity. Furthermore, we find that a lack of tonic adenosine inhibition enables this high probability of release and, consequently, recurrent network activity.
Expanding the CITE-seq tool-kit: Detection of proteins, transcriptomes, clonotypes and CRISPR perturbations with multiplexing, in a single assay
Authors: Mimitou Eleni , Cheng Anthony , Montalbano Antonino , Hao Stephanie , Stoeckius Marlon , Legut Mateusz , Roush Timothy , Herrera Alberto , Papalexi Efthymia , Ouyang Zhengquing , Satija Rahul , Sanjana Neville E. , Koralov Sergei B , Smibert Peter 
Published: November 2018

ABSTRACTRapid technological progress in the recent years has allowed the high-throughput interrogation of different types of biomolecules from single cells. Combining several of these readouts into integrated multi-omic assays is essential to comprehensively understand and model cellular processes. Here, we report the development of Expanded CRISPR-compatible Cellular Indexing of Transcriptomes and Epitopes by sequencing (ECCITE-seq) for the high-throughput characterization of at least five modalities of information from each single cell: transcriptome, immune receptor clonotypes, surface markers, sample identity and sgRNAs. We demonstrate the use of ECCITE-seq to directly and efficiently capture sgRNA molecules and measure their effects on gene expression and protein levels, opening the possibility of performing high throughput single cell CRISPR screens with multimodal readout using existing libraries and commonly used vectors. Finally, by utilizing the combined phenotyping of clonotype and cell surface markers in immune cells, we apply ECCITE to study a lymphoma sample to discriminate cells and define molecular signatures of malignant cells within a heterogeneous population.
The use of environmental performance indicators in “the greenest city in Europe”
Authors: Alpenberg Jan , Wnuk-Pel Tomasz , Adamsson Philip , Petersson Johannes 
Published: November 2018

Purpose
The purpose of this paper is to examine why and how municipal managers and CEOs for municipally owned companies use the environmental performance indicators.

Design/methodology/approach
A case study approach as a research design was used. In total, 18 semi-structured interviews were conducted among managers for administrative departments and municipal company CEOs.

Findings
This study found that the environmental performance indicators are used by department managers mainly for resource allocation, control and for teaching the employees. The CEOs of the municipal companies use the environmental indicators for communicating with external stakeholders and see the indicators primarily as marketing tools. The main reason why the environmental performance indicators are used in the municipality can be the strong demand from the local politicians to push the “green agenda,” and therefore the managers have to comply.

Research limitations/implications
As in any case study, generalizations from the research should be made with care, but since this is only one municipality, further research is needed to find additional evidence.

Practical implications
The findings of this study have a number of implications for future practice, and it is worth mentioning that clear guidelines for how the information could be made more useful for managers at the managerial level in Växjö municipality (VM) are requested for both the municipal managers and the CEOs.

Social implications
Overall, this study strengthens the idea that environmental performance indicators could be used to a larger extent for communicating with external stakeholders both for municipal departments and companies.

Originality/value
The research adds to the literature by examining different patterns of using environmental performance indicators in a unique setting – in VM, which is called “the greenest city in Europe” and is one of the “pioneers” in environmental work and extensively uses performance indicators.