bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sharpening of hierarchical visual feature representations of blurred images
Authors: Abdelhack Mohamed , Kamitani Yukiyasu 
Published: December 2017

AbstractThe robustness of the visual system lies in its ability to perceive degraded images. This is achieved through interacting bottom-up, recurrent, and top-down pathways that process the visual input in concordance with stored prior information. The interaction mechanism by which they integrate visual input and prior information is still enigmatic. We present a new approach using deep neural network (DNN) representation to reveal the effects of such integration on degraded visual inputs. We transformed measured human brain activity resulting from viewing blurred images to the hierarchical representation space derived from a feedforward DNN. Transformed representations were found to veer towards the original non-blurred image and away from the blurred stimulus image. This indicated deblurring or sharpening in the neural representation, and possibly in our perception. We anticipate these results will help unravel the interplay mechanism between bottom-up, recurrent, and top-down pathways, leading to more comprehensive models of vision.Significance statementOne powerful characteristic of the visual system is its ability to complement visual information for incomplete visual images. It operates by projecting information from higher visual and semantic areas of the brain into the lower and mid-level representations of the visual stimulus. We investigate the mechanism by which the human brain represents blurred visual stimuli. By decoding fMRI activity into a feedforward-only deep neural network reference space, we found that neural representations of blurred images are biased towards their corresponding deblurred images. This indicates a sharpening mechanism occurring in the visual cortex.
Zebrafish differentially process colour across visual space to match natural scenes
Authors: Zimmermann Maxime JY , Nevala Noora E , Yoshimatsu Takeshi , Osorio Daniel , Nilsson Dan-Eric , Berens Philipp , Baden Tom 
Published: December 2017

SummaryAnimal eyes evolve to process behaviourally important visual information, but how retinas deal with statistical asymmetries in visual space remains poorly understood. Using hyperspectral imaging in the field,in-vivo2-photon imaging of retinal neurons and anatomy, here we show that larval zebrafish use a highly anisotropic retina to asymmetrically survey their natural visual world. First, different neurons dominate different parts of the eye, and are linked to a systematic shift in inner retinal function: Above the animal, there is little colour in nature and retinal circuits are largely achromatic. Conversely, the lower visual field and horizon are colour-rich, and are predominately surveyed by chromatic and colour-opponent circuits that are spectrally matched to the dominant chromatic axes in nature. Second, above the frontal horizon, a high-gain ultraviolet-system piggy-backs onto retinal circuits, likely to support prey-capture. Our results demonstrate high functional diversity among single genetically and morphologically defined types of neurons.
What does not kill a tumour may make it stronger:in silicoInsights into Chemotherapeutic Drug Resistance
Authors: Hamis Sara , Nithiarasu Perumal , Powathil Gibin G 
Published: December 2017

AbstractTumour recurrence post chemotherapy is an established clinical problem and many cancer types are often observed to be increasingly drug resistant subsequent to chemotherapy treatments. Drug resistance in cancer is a multipart phenomenon which can be derived from several origins and in many cases it has been observed that cancer cells have the ability to possess, acquire and communicate drug resistant traits.Here, anin silicoframework is developed in order to study drug resistance and drug response in cancer cell populations exhibiting various drug resistant features. The framework is based on an on-lattice hybrid multiscale mathematical model and is equipped to simulate multiple mechanisms on different scales that contribute towards chemotherapeutic drug resistance in cancer. This study demonstrates how drug resistant tumour features may depend on the interplay amongst intracellular, extracelluar and intercellular factors. On a cellular level, drug resistant cell phenotypes are here derived from inheritance or mutations that are spontaneous, drug-induced or communicated via exosomes. Furthermore intratumoural heterogeneity and spatio-temporal drug dynamics heavily influences drug delivery and the development of drug resistant cancer cell subpopulations. Chemotherapy treatment strategies are here optimised for variousin silicotumour scenarios and treatment objectives. We demonstrate that optimal chemotherapy treatment strategies drastically depend on which drug resistant mechanisms are activated, and that furthermore suboptimal chemotherapy administration may promote drug resistance.
Mutation accumulation in selfing populations under fluctuating selection
Authors: Ho Eddie K.H. , Agrawal Aneil F. 
Published: December 2017

AbstractSelfing species are prone to extinction, possibly because highly selfing populations can suffer from a continuous accumulation of deleterious mutations, a process analogous to Muller’s ratchet in asexual populations. However, current theory provides little insight into which types of genes are most likely to accumulate deleterious alleles and what environmental circumstances may accelerate genomic degradation. Here we investigate temporal changes in the environment that cause fluctuations in the strength of purifying selection. We simulate selfing populations with genomes containing a mixture of loci experiencing constant selection and loci experiencing selection that fluctuates in strength (but not direction). Even when both types of loci experience the same average strength of selection, loci under fluctuating selection contribute disproportionately more to deleterious mutation accumulation. Moreover, the presence of loci experiencing fluctuating selection in the genome increases the deleterious fixation rate at loci under constant selection; under most realistic scenarios this effect of linked selection can be attributed to a reduction inNe. Fluctuating selection is particularly injurious when selective environments are strongly autocorrelated over time and when selection is concentrated into rare bouts of strong selection. These results imply that loci under fluctuating selection are likely important drivers of extinction in selfing species.
AVery Oil Yellow1modifier of theOil Yellow1-N1989allele uncovers a cryptic phenotypic impact of cis-regulatory variation in maize
Authors: Khangura Rajdeep S. , Marla Sandeep , Venkata Bala P. , Heller Nicholas J. , Johal Gurmukh S. , Dilkes Brian P. 
Published: December 2017

AbstractForward genetics determines the function of genes underlying trait variation by identifying the change in DNA responsible for changes in phenotype. Detecting phenotypically-relevant variation outside protein coding sequences and distinguishing this from neutral variants is not trivial; partly because the mechanisms by which DNA polymorphisms in the intergenic regions affect gene regulation are poorly understood. Here we utilized a dominant genetic marker with a convenient phenotype to investigate the effect of cis and trans-acting regulatory variation. We performed a forward genetic screen for natural variation that suppress or enhance the semi-dominant mutant alleleOy1-N1989,encoding the magnesium chelatase subunit I of maize. This mutant permits rapid phenotyping of leaf color as a reporter for chlorophyll accumulation, and mapping of natural variation in maize affecting chlorophyll metabolism. We identified a single modifier locus segregating between B73 and Mo17 that was linked to the reporter gene itself, which we callvery oil yellow1. Based on the variation in OY1 transcript abundance and genome-wide association data,vey1is predicted to consist of multiple cis-acting regulatory sequence polymorphisms encoded at the wild-typeoy1alleles. Thevey1allele appears to be a common polymorphism in the maize germplasm that alters the expression level of a key gene in chlorophyll biosynthesis. Thesevey1alleles have no discernable impact on leaf chlorophyll in the absence of theOy1-N1989reporter. Thus, use of a mutant as a simple and efficient reporter for magnesium chelatase activity resulted in the detection of expression-level polymorphisms not readily visible in the laboratory.
Cell Lysate Microarray for Mapping the Network of Genetic Regulators for Histone Marks
Authors: Cheng Li , Liu Cheng-xi , Jiang Shuang-ying , Hou Sha , Huang Jin-guo , Chen Zi-qing , Sun Yang-yang , Qi Huan , Jiang He-wei , Wang Jing-fang , Zhou Yi-ming , Czajkowsky Daniel M , Dai Jun-biao , Tao Sheng-ce 
Published: December 2017

SUMMARYProtein, as the major executer for cell progresses and functions, its abundance and the level of post-translational modifications, are tightly monitored by regulators. Genetic perturbation could help us to understand the relationships between genes and protein functions. Herein, we developed a cell lysate microarray on kilo-conditions (CLICK) from 4,837 yeast knockout (YKO) strains and 322 temperature-sensitive mutant strains to explore the impact of the genome-wide interruption on certain protein. Taking histone marks as examples, a general workflow was established for the global identification of upstream regulators. Through a single CLICK array test, we obtained a series of regulators for H3K4me3 which covers most of the known regulators in Saccharomyces cerevisiae. We also noted that several group of proteins that are linked to negatively regulation of H3K4me3. Further, we discovered that Cab4p and Cab5p, two key enzymes of CoA biosynthesis, play central roles in histone acylation. Because of its general applicability, CLICK array could be easily adopted to rapid and global identification of upstream protein/enzyme(s) that regulate/modify the level of a protein or the posttranslational modification of a non-histone protein.
Increasing sensitivity and accuracy of brain-wide quantitative studies in light-sheet microscopy
Authors: Müllenbroich Caroline M. , Silvestri Ludovico , Turrini Lapo , Alterini Tommaso , Di Giovanna Antonino P. , Costantini Irene , Gheisari Ali , Vanzi Francesco , Sacconi Leonardo , Pavone Francesco S. 
Published: December 2017

AbstractLight-sheet microscopy (LSM) has proven a useful tool in neuroscience to image whole brains with high frame rates at cellular resolution. LSM is employed either in combination with tissue clearing to reconstruct the cyto-architecture over the entire mouse brain or with intrinsically transparent samples like zebrafish larvae for functional imaging. Inherently to LSM, however, residual opaque objects cause stripe artifacts, which obscure features of interest and, during functional imaging, modulate fluorescence variations related to neuronal activity. Here, we report how Bessel beams reduce streaking artifacts and produce high-fidelity structural data. Furthermore, using Bessel beams, we demonstrate a fivefold increase in sensitivity to calcium transients and a 20 fold increase in accuracy in the detection of activity correlations in functional imaging. Our results demonstrate the contamination of data by systematic and random errors through Gaussian illumination and furthermore quantify the increase in fidelity of such data when using Bessel beams.
Planning and navigation as active inference
Authors: Kaplan Raphael , Friston Karl J 
Published: December 2017

AbstractThis paper introduces an active inference formulation of planning and navigation. It illustrates how the exploitation–exploration dilemma is dissolved by acting to minimise uncertainty (i.e., expected surprise or free energy). We use simulations of a maze problem to illustrate how agents can solve quite complicated problems using context sensitive prior preferences to form subgoals. Our focus is on how epistemic behaviour – driven by novelty and the imperative to reduce uncertainty about the world – contextualises pragmatic or goal-directed behaviour. Using simulations, we illustrate the underlying process theory with synthetic behavioural and electrophysiological responses during exploration of a maze and subsequent navigation to a target location. An interesting phenomenon that emerged from the simulations was a putative distinction between ‘place cells’ – that fire when a subgoal is reached – and ‘path cells’ – that fire until a subgoal is reached.
Correlated disasters and need-based transfers: The limits of risk pooling systems in simulated ecologies
Authors: Campenni Marco , Cronk Lee , Aktipis Athena 
Published: December 2017

ABSTRACTThroughout their evolutionary history, humans have faced risks including drought, disease, natural disasters and other unexpected negative events. To deal with these risks, humans use a variety of risk management strategies, some of which involve relying on others in times of need in order to pool risk. However, the effectiveness of risk pooling strategies can be limited when there is high synchronicity of need. Here we investigate the limits of two resource transfer systems for pooling risk (need-based transfers, NBT, and debt-based transfers, DBT) in simulated ecologies with different degrees of correlated disasters using an agent-based model of the need-based transfer system of the Maasai. Overall, we find that survival is higher when shocks are less correlated among partners, when groups are larger, and when network structure is characterized by preferential attachment networks, which have a more modular structure than regular or small world networks. We also find that NBT strategies consistently outperform DBT strategies across a wide variety of parameter values and that the advantage of NBT over DBT is greatest when shocks are less correlated and group size is small. Our results also suggest that systems of sharing that are based on recipient need are less vulnerable than systems that are based on debt and credit, especially in small world and regular networks.
Dual tRNA mimicry in the Cricket Paralysis Virus IRES uncovers an unexpected similarity with the Hepatitis C Virus IRES
Authors: Pisareva Vera P. , Pisarev Andrey. V. , Fernández Israel S. 
Published: December 2017

AbstractCo-opting the cellular machinery for protein production is a compulsory requirement for viruses. The Cricket Paralysis virus employs an Internal Ribosomal Entry Site (IRES) to express its structural genes in the late stage of infection. Ribosome hijacking is achieved by a sophisticated use of molecular mimicry to tRNA and mRNA, employed to manipulate intrinsically dynamic components of the ribosome. Binding and translocation through the ribosome is required for this IRES to initiate translation. We report two structures, solved by single particle electron cryomicroscopy (cryoEM), of a double translocated CrPV IRES with aminoacyl-tRNA in the peptidyl site (P site) of the ribosome. CrPV IRES adopts a previously unseen conformation, mimicking the acceptor stem of a canonical E site tRNA. The structures suggest a mechanism for the positioning of the first aminoacyl-tRNA shared with the distantly related Hepatitis C Virus IRES.
NuMA is a negative regulator of 53BP1 in DNA double-strand break repair
Authors: Salvador-Moreno Naike , Liu Jing , Haas Karen M. , Parker Laurie L. , Chakraborty Chaitali , Kron Stephen J. , Hodges Kurt , Miller Lance D. , Robinson Paul J. , Leliévre Sophie A. , Vidi Pierre-Alexandre 
Published: December 2017

AbstractAccumulation of 53BP1 at DNA breaks determines DNA repair pathway choice and promotes checkpoint activation. Here, we show regulation of 53BP1 beyond repair foci. 53BP1 movements are constrained in the nucleoplasm and increase in response to DNA damage. 53BP1 interacts with the structural protein NuMA, which controls 53BP1 diffusion. This interaction, and colocalization between the two proteins in vitro and in breast tissues, is reduced after DNA damage. In cell lines and breast carcinoma, NuMA prevents 53BP1 accumulation at DNA breaks and high NuMA expression predicts better patient outcomes. Manipulating NuMA expression alters PARP inhibitor sensitivity of BRCA1-null cells, end-joining activity, and immunoglobulin class switching that rely on 53BP1. We propose a new mechanism that involves the sequestration of 53BP1 by NuMA in the absence of DNA damage. Such mechanism may have evolved to disable repair functions and may be a decisive factor for tumor responses to genotoxic treatments.
Formation of correlated chromatin domains at nanoscale dynamic resolution during transcription
Authors: Shaban Haitham A. , Barth Roman , Bystricky Kerstin 
Published: December 2017

AbstractIntrinsic dynamics of chromatin contribute to gene regulation. How chromatin mobility responds to genomic processes and whether this response relies on coordinated movement is still unclear. Here, we introduce an approach called Dense Flow reConstruction and Correlation (DFCC) to quantify correlation of chromatin motion with sub-pixel sensitivity at the level of the whole nucleus. DFCC is based on reconstructing dense global flow fields of fluorescent images acquired in real-time. By simulating variations in microscopic and dynamic parameters, we demonstrate that our approach is robust and more accurate than other methods to estimate flow fields and spatial correlations of dense structures such as chromatin. We applied our approach to analyze stochastic movements of DNA and histones based on direction and magnitude at different time lags in human cells. We observe long-range correlations extending over several μm between coherently moving regions over the entire nucleus. Spatial correlation of global chromatin dynamics was reduced by inhibiting elongation by RNA polymerase II and abolished in quiescent cells. Furthermore, quantification of spatial smoothness over time intervals up to 30 seconds points to clear-cut boundaries between distinct regions, while smooth transitions in small (<1 μm) neighborhoods dominate for short time intervals. Clear transitions between regions of coherent motion indicate directed squeezing or stretching of chromatin boundaries suggestive of changes in local concentrations of actors regulating gene expression. The DFCC approach hence allows characterizing stochastically forming domains of specific nuclear activity.Significance StatementControl of gene expression relies on modifications of chromatin structure and activity of the transcription machinery. However, how chromatin responds dynamically to this genomic process and whether this response is coordinated in space is still unclear. We introduce a novel approach called Dense Flow reConstruction and Correlation (DFCC) to characterize spatially correlated dynamics of chromatin in living cells at nanoscale resolution. DFCC allows us to detect chromatin domains in living cells with long range correlations over the entire nucleus. Furthermore, transitions between domains can be quantified by the newly introduced smoothness parameter of local chromatin motion. The DFCC approach permits characterizing stochastically forming domains of other DNA dependent activity in any cell type in real time imaging.
The Relation Between α-Helical Conformation and Amyloidogenicity
Authors: Haimov B. , Srebnik S. 
Published: December 2017

ABSTRACTAmyloid fibrils are stable aggregates of misfolded proteins and polypeptides that are insoluble and resistant to protease activity. Abnormal formation of amyloid fibrils in vivo may lead to neurodegenerative disorders and other systemic amyloidosis such as Alzheimer’s, Parkinson’s, and atherosclerosis. Because of their clinical importance amyloids are found under intense scientific research. Amyloidogenic sequences of short polypeptide segments within proteins are responsible for the transformation of correctly folded proteins into parts of larger amyloid fibrils. The α-helical secondary structure is believed to host many amyloidogenic sequences and be a key player in different stages of the amyloidogenesis process. Most of the studies on amyloids focus on the role of amyloidogenic sequences. The focus of this study is the relation between amyloidogenicity and the structure of the amyloidogenic α-helical sequence. We have previously shown that the α-helical conformation may be expressed by two parameters (θ and ρ) that form orthogonal coordinates based on the Ramachandran dihedrals (φ and ψ) and provide an illuminating interpretation of the α-helical conformation. By performing statistical analysis on α-helical conformations found in the protein data bank, an apparent relation between α-helical conformation, as expressed by θ and ρ, and amyloidogenicity is revealed. Remarkably, random amino acid sequences, whose helical structure was obtained from the most probably dihedral angles as obtained from PDB data, revealed the same dependency of amyloidogenicity, suggesting the importance of α-helical structure as opposed to sequence.
Differential expression analysis of log-ratio transformed counts: benchmarking methods for RNA-Seq data
Authors: Quinn Thomas P. , Crowley Tamsyn M. , Richardson Mark F. 
Published: December 2017

AbstractBackgroundCount data generated by next-generation sequencing assays do not measure absolute transcript abundances. Instead, the data are constrained to an arbitrary “library size” by the sequencing depth of the assay, and typically must be normalized prior to statistical analysis. The constrained nature of these data means one could alternatively use a log-ratio transformation in lieu of normalization, as often done when testing for differential abundance (DA) of operational taxonomic units (OTUs) in 16S rRNA data. Therefore, we benchmark how well the ALDEx2 package, a transformation-based DA tool, detects differential expression in high-throughput RNA-sequencing data (RNA-Seq), compared to conventional RNA-Seq differential expression methods.ResultsTo evaluate the performance of log-ratio transformation-based tools, we apply the ALDEx2 package to two simulated, and one real, RNA-Seq data sets. The latter was previously used to benchmark dozens of conventional RNA-Seq differential expression methods, enabling us to directly compare transformation-based approaches. We show that ALDEx2, widely used in meta-genomics research, identifies differentially expressed genes (and transcripts) from RNA-Seq data with high precision and, given sufficient sample sizes, high recall too (regardless of the alignment and quantification procedure used). Although we show that the choice in log-ratio transformation can affect performance, ALDEx2 has high precision (i.e., few false positives) across all transformations. Finally, we present a novel, iterative log-ratio transformation (now implemented in ALDEx2) that further improves performance in simulations.ConclusionsOur results suggest that log-ratio transformation-based methods can work to measure differential expression from RNA-Seq data, provided that certain assumptions are met. Moreover, these methods have high precision (i.e., few false positives) in simulations and perform as good as, or better than, than conventional methods on real data. With previously demonstrated applicability to 16S rRNA data, ALDEx2 can work as a single tool for data from multiple sequencing modalities.