bluuebunny/crossref_metadata_2025_split huggingface dataset:
Molecular interactions in nanocellulose assembly
Authors: Nishiyama Yoshiharu 
Published: December 2017

The contribution of hydrogen bonds and the London dispersion force in the cohesion of cellulose is discussed in the light of the structure, spectroscopic data, empirical molecular-modelling parameters and thermodynamics data of analogue molecules. The hydrogen bond of cellulose is mainly electrostatic, and the stabilization energy in cellulose for each hydrogen bond is estimated to be between 17 and 30 kJ mol
−1
. On average, hydroxyl groups of cellulose form hydrogen bonds comparable to those of other simple alcohols. The London dispersion interaction may be estimated from empirical attraction terms in molecular modelling by simple integration over all components. Although this interaction extends to relatively large distances in colloidal systems, the short-range interaction is dominant for the cohesion of cellulose and is equivalent to a compression of 3 GPa. Trends of heat of vaporization of alkyl alcohols and alkanes suggests a stabilization by such hydroxyl group hydrogen bonding to be of the order of 24 kJ mol
−1
, whereas the London dispersion force contributes about 0.41 kJ mol
−1
Da
−1
. The simple arithmetic sum of the energy is consistent with the experimental enthalpy of sublimation of small sugars, where the main part of the cohesive energy comes from hydrogen bonds. For cellulose, because of the reduced number of hydroxyl groups, the London dispersion force provides the main contribution to intermolecular cohesion.

This article is part of a discussion meeting issue ‘New horizons for cellulose nanotechnology’.
Clustering enzymes using E.coli inner cell membrane as scaffold in metabolic pathway
Authors: Wang You , Wu Yuqi , Suo Yang , Guo Huaqing , Yu Yineng , Yin Ruonan , Xi Rui , Wu Jiajie , Hua Nan , Zhang Yuehan , Zhang Shaobo , Jin Zhenming , Wang Yushu , He Lin , Ma Gang 
Published: December 2017

AbstractClustering enzymes in the same metabolism pathway is a natural strategy to enhance the productivity. Several systems have been designed to artificially cluster desired enzymes in the cell, such as synthetic protein scaffold and nucleic acid scaffold. However, these scaffolds require complicated construction process and have limited slots for target enzymes. Following this direction, we designed a scaffold system based on natural cell membrane. Target enzymes (FabZ, FabG, FabI and TesA’ in fatty acid synthesis II pathway) are anchored on the E.coli inner membrane, showing the enhanced metabolism flux without the requirement of the further artificial interactions to force the clustering. Furthermore, anchoring the enzymes on the membrane enhances the products exportation, which further increases the productivity. Together, the proposed system has potential applications in producing valuable biomaterials.
Genome-wide stability of the DNA replication program in single mammalian cells
Authors: Takahashi Saori , Miura Hisashi , Shibata Takahiro , Nagao Koji , Okumura Katsuzumi , Ogata Masato , Obuse Chikashi , Takebayashi Shin-ichiro , Hiratani Ichiro 
Published: December 2017

ABSTRACTHere, we report the establishment of asingle-cell DNAreplicationsequencing method, scRepli-seq, which is a simple genome-wide methodology that measures copy number differences between replicated and unreplicated DNA. Using scRepli-seq, we demonstrate that replication domain organization is conserved among individual mouse embryonic stem cells (mESCs). Differentiated mESCs exhibited distinct replication profiles, which were conserved from cell to cell. Haplotype-resolved scRepli-seq revealed similar replication timing profiles of homologous autosomes, while the inactive X chromosome was clearly replicated later than its active counterpart. However, a small degree of cell-to-cell replication timing heterogeneity was present, and we discovered that developmentally regulated domains are a source of such variability, suggesting a link between cell-to-cell heterogeneity and developmental plasticity. Together, our results form a foundation for single-cell-level understanding of DNA replication regulation and provide insights into 3D genome organization.
Caste-biased movements by termites in isolation
Authors: Hiroyuki Shimoji , Nobuaki Mizumoto , Kohei Oguchi , Shigeto Dobata 
Published: December 2017

AbstractThe caste system of termites is an example of phenotypic plasticity. The castes differ not only in morphology and physiology, but also in behavior. As most of their behaviors within colonies involve nestmates, it is difficult to extract innate differences among castes. In this study, we focused on movement patterns of isolated individuals ofHodotermopsis sjostedti. We observed distinct clusters in movement patterns over 30 min, which indicates that termites have multiple innate modes of movement. The use of these modes is biased among castes, among which neotenics had a caste-specific mode and soldiers moved more actively than workers or neotenics. These caste biases may reflect different adaptive responses to social isolation. Our study provides a basis for a deeper understanding of the roles of individual movements in social behaviors.Summary StatementMovement patterns of termites in isolation were described for different castes. We proposed movements as a novel caste-specific characteristics in social insects.
Epigenomic and genomic landscape ofDrosophila melanogasterheterochromatic genes
Authors: Saha Parna , Sowpati Divya Tej , Mishra Rakesh K 
Published: December 2017

AbstractHeterochromatin is associated with transcriptional repression. In contrast, several genes in the pericentromeric regions ofDrosophila melanogasterare dependent on this heterochromatic environment for their expression. Heterochromatic genes encode proteins involved in various developmental processes. Several studies have shown that a variety of epigenetic modifications is associated with these genes. Here we present a comprehensive analysis of the epigenetic landscape of heterochromatic genes across all the developmental stages ofDrosophilausing the available histone modification and expression data from modENCODE. We find that heterochromatic genes exhibit combinations of active and inactive histone marks that correspond to their level of expression during development. Thus, we classified these genes into three groups based on the combinations of histone modifications present. We also looked for potential regulatory DNA sequence elements in the genomic neighborhood of these genes. Our results show that NuclearMatrixAssociatedRegions (MARs) are prominently present in the intergenic regions of heterochromatic genes during embryonic stages suggesting their plausible role in pericentromeric genome organization. We also find that the intergenic sequences in the heterochromatic regions have binding sites for transcription factors known to modulate epigenetic status. Taken together, our meta-analysis of the various genomic datasets suggest that the epigenomic and genomic landscape of the heterochromatic genes are distinct from that of euchromatic genes. These features could be contributing to the unusual regulatory status of the heterochromatic genes as opposed to the surrounding heterochromatin, which is repressive in nature.
Active learning reveals underlying decision strategies
Authors: Parpart Paula , Schulz Eric , Speekenbrink Maarten , Love Bradley C. 
Published: December 2017

AbstractOne key question is whether people rely on frugal heuristics orfull-informationstrategies when making preference decisions. We propose a novel method,model-based active learning, to answer whether people conform more to a rank-based heuristic (Take-The-Best) or a weight-based full-information strategy (logistic regression). Our method eclipses traditional model comparison techniques by using information theory to characterize model predictions for how decision makers should actively sample information. These analyses capture how sampling affects learning and how learning affects decisions on subsequent trials. We develop and test model-based active learning algorithms for both Take-The-Best and logistic regression. Our findings reveal that people largely follow a weight-based learning strategy rather than a rank-based strategy, even in cases where their preference decisions are better predicted by the Take-The-Best heuristic. This finding suggests that people may have more refined knowledge than is revealed by their preference decisions, but which can be revealed by their information sampling behavior. We argue that model-based active learning is an effective and sensitive method for model selection that expands the basis for model comparison.
AMBER: Assessment of Metagenome BinnERs
Authors: Meyer Fernando , Hofmann Peter , Belmann Peter , Garrido-Oter Ruben , Fritz Adrian , Sczyrba Alexander , McHardy Alice C. 
Published: December 2017

AbstractReconstructing the genomes of microbial community members is key to the interpretation of shotgun metagenome samples. Genome binning programs deconvolute reads or assembled contigs of such samples into individual bins, but assessing their quality is difficult due to the lack of evaluation software and standardized metrics. We present AMBER, an evaluation package for the comparative assessment of genome reconstructions from metagenome benchmark data sets. It calculates the performance metrics and comparative visualizations used in the first benchmarking challenge of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI). As an application, we show the outputs of AMBER for ten different binnings on two CAMI benchmark data sets. AMBER is implemented in Python and available under the Apache 2.0 license on GitHub (https://github.com/CAMI-challenge/AMBER).
Rethinking dopamine as generalized prediction error
Authors: Gardner Matthew P.H. , Schoenbaum Geoffrey , Gershman Samuel J. 
Published: December 2017

AbstractMidbrain dopamine neurons are commonly thought to report a reward prediction error, as hypothesized by reinforcement learning theory. While this theory has been highly successful, several lines of evidence suggest that dopamine activity also encodes sensory prediction errors unrelated to reward. Here we develop a new theory of dopamine function that embraces a broader conceptualization of prediction errors. By signaling errors in both sensory and reward predictions, dopamine supports a form of reinforcement learning that lies between model-based and model-free algorithms. This account remains consistent with current canon regarding the correspondence between dopamine transients and reward prediction errors, while also accounting for new data suggesting a role for these signals in phenomena such as sensory preconditioning and identity unblocking, which ostensibly draw upon knowledge beyond reward predictions.
Equivalent high-resolution identification of neuronal cell types with single-nucleus and single-cell RNA-sequencing
Authors: Bakken Trygve E. , Hodge Rebecca D. , Miller Jeremy M. , Yao Zizhen , Nguyen Thuc N. , Aevermann Brian , Barkan Eliza , Bertagnolli Darren , Casper Tamara , Dee Nick , Garren Emma , Goldy Jeff , Gray Lucas T. , Kroll Matthew , Lasken Roger S. , Lathia Kanan , Parry Sheana , Rimorin Christine , Scheuermann Richard H. , Schork Nicholas J. , Shehata Soraya I. , Tieu Michael , Phillips John W. , Bernard Amy , Smith Kimberly A. , Zeng Hongkui , Lein Ed S. , Tasic Bosiljka 
Published: December 2017

AbstractTranscriptional profiling of complex tissues by RNA-sequencing of single nuclei presents some advantages over whole cell analysis. It enables unbiased cellular coverage, lack of cell isolation-based transcriptional effects, and application to archived frozen specimens. Using a well-matched pair of single-nucleus RNA-seq (snRNA-seq) and single-cell RNA-seq (scRNA-seq) SMART-Seq v4 datasets from mouse visual cortex, we demonstrate that similarly high-resolution clustering of closely related neuronal types can be achieved with both methods if intronic sequences are included in nuclear RNA-seq analysis. More transcripts are detected in individual whole cells (∼11,000 genes) than nuclei (∼7,000 genes), but the majority of genes have similar detection across cells and nuclei. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues.
Rethinking “normal”: The role of stochasticity in the phenology of a synchronously breeding seabird
Authors: Youngflesh Casey , Jenouvrier Stephanie , Hinke Jefferson T. , DuBois Lauren , St. Leger Judy , Trivelpiece Wayne Z. , Trivelpiece Susan G. , Lynch Heather J. 
Published: December 2017

Abstract

Phenological changes have been observed in a variety of systems over the past century. There is concern that, as a consequence, ecological interactions are becoming increasingly mismatched in time, with negative consequences for ecological function.

Significant spatial heterogeneity (inter‐site) and temporal variability (inter‐annual) can make it difficult to separate intrinsic, extrinsic and stochastic drivers of phenological variability. The goal of this study was to understand the timing and variability in breeding phenology of Adélie penguins under fixed environmental conditions and to use those data to identify a “null model” appropriate for disentangling the sources of variation in wild populations.

Data on clutch initiation were collected from both wild and captive populations of Adélie penguins. Clutch initiation in the captive population was modelled as a function of year, individual and age to better understand phenological patterns observed in the wild population.

Captive populations displayed as much inter‐annual variability in breeding phenology as wild populations, suggesting that variability in breeding phenology is the norm and thus may be an unreliable indicator of environmental forcing. The distribution of clutch initiation dates was found to be moderately asymmetric (right skewed) both in the wild and in captivity, consistent with the pattern expected under social facilitation.

The role of stochasticity in phenological processes has heretofore been largely ignored. However, these results suggest that inter‐annual variability in breeding phenology can arise independent of any environmental or demographic drivers and that synchronous breeding can enhance inherent stochasticity. This complicates efforts to relate phenological variation to environmental variability in the wild. Accordingly, we must be careful to consider random forcing in phenological processes, lest we fit models to data dominated by random noise. This is particularly true for colonial species where breeding synchrony may outweigh each individual's effort to time breeding with optimal environmental conditions. Our study highlights the importance of identifying appropriate null models for studying phenology.
Transient movements of a deep‐water flatfish in coastal waters: Implications of inshore‐offshore connectivity for fisheries management
Authors: Barkley Amanda N. , Fisk Aaron T. , Hedges Kevin J. , Treble Margaret A. , Hussey Nigel E. 
Published: December 2017

Abstract

Globally, small‐scale inshore fisheries are being recognized as highly beneficial for underdeveloped coastal communities since they directly contribute to local economies. Community coastal fisheries, however, may target species that are simultaneously harvested by large commercial vessels in adjacent offshore waters, creating uncertainty over stock units and connectivity that complicate management.

Greenland halibut Reinhardtius hippoglossoides, a commercially important flatfish species in the Arctic, were tagged in Scott Inlet, coastal Baffin Island, Canada, with acoustic transmitters and tracked for a 1‐year period. Our aim was to measure fish movement and connectivity between inshore habitats, where Inuit fisheries are developing, and offshore waters, where an established commercial fishery operates. Four movement metrics were established, and cluster analysis and a mixed effects model were used to define movement types and identify environmental covariates of the presence/absence within the coastal environment respectively.

Two distinct movement patterns were characterized for Greenland halibut; the majority were transients that were no longer detected inshore by the end of November (n = 47, 72%), and a smaller group of intermittently resident fish that moved into the offshore at the same time as transient fish, but returned to the coastal environment in the winter (n = 8, 12%), with the remainder being undefined. The presence of Greenland halibut in the inshore was negatively correlated with ice cover, indicating that fish moved offshore as sea ice formed.

Synthesis and applications. Greenland halibut were previously thought to be highly resident within the coastal environment of Baffin Bay; however, our data demonstrates that this is not true for all areas. In Scott Inlet and adjacent coastal regions, Greenland halibut exhibit complex inshore‐offshore connectivity, suggesting inshore and offshore fisheries require a shared quota. We recommend that in the face of developing global small‐scale coastal fisheries, improved understanding of stock connectivity between environments is required to sustainably manage commercial fish species.
Effects of small‐scale, shading‐induced seagrass loss on blue carbon storage: Implications for management of degraded seagrass ecosystems
Authors: Trevathan‐Tackett Stacey M. , Wessel Caitlin , Cebrián Just , Ralph Peter J. , Masqué Pere , Macreadie Peter I. 
Published: December 2017

Abstract

Seagrass meadows are important global blue carbon sinks. Despite a 30% loss of seagrasses globally during the last century, there is limited empirical research investigating the effects of disturbance and loss of seagrass on blue carbon stocks.

In this study, we hypothesised that seagrass loss would reduce blue carbon stocks. Using shading cloth, we simulated small‐scale die‐offs of two subtropical seagrass species, Halodule wrightii and Thalassia testudinum, in a dynamic northern Gulf of Mexico lagoon. The change in quantity and quality of sediment organic matter (OM) and organic carbon was compared among die‐off, control and bare plots before the die‐off treatment, shortly after the die‐off treatment and 11 months after the die‐off treatment. 210Pb age dating was performed on bare and Thalassia plots at 11 months to evaluate the impact of sediment erosion in the absence of vegetation.

The small‐scale die‐off led to a 50%–65% OM loss in the sediment in the top 8 cm of Halodule plots. Thalassia plots lost significant portions of OM (50%) and organic carbon (Corg; 21%–47%) in only the top 1 cm of sediment. The 210Pb profiles indicated Thalassia die‐off reduced the Corg sequestration rate by 10%, in addition to a loss of c. 1 year's worth of Corg stocks (c. 22 g/m2). Furthermore, analyses on OM/Corg quality indicated a loss of labile OM/Corg and enhanced remineralisation by microbes.

Synthesis and applications. This study provides empirical evidence that small‐scale shading‐induced seagrass die‐offs can reduce seagrass carbon sequestration capacity and trigger losses of blue carbon stocks. While the losses recorded here are modest, these losses in blue carbon storage capacity are notable due to the proximity of shading structures (e.g. boat docks) to seagrass habitats. Thus, policies to avoid or protect seagrass habitats from common small‐scale, shading disturbances are important for optimising both carbon sequestration capacity and coastline development and management.
Nutrient limitation or home field advantage: Does microbial community adaptation overcome nutrient limitation of litter decomposition in a tropical peatland?
Authors: Hoyos‐Santillan Jorge , Lomax Barry H. , Turner Benjamin L. , Sjögersten Sofie 
Published: December 2017

Abstract

Litter decomposition is an important control on carbon accumulation in tropical peatlands. Stoichiometric theory suggests that decomposition is regulated by elemental ratios in litter while the home field advantage (HFA) hypothesis predicts that decomposer communities are adapted to local conditions. To date, the relative importance of these contrasting theories for litter decomposition and therefore the carbon balance of tropical peatlands remain poorly understood.

We conducted two in situ litter decomposition experiments in a lowland tropical peatland. The first experiment tested the importance of the stoichiometric theory using a factorial nutrient addition experiment at two sites with contrasting vegetation (Raphia taedigera and Campnosperma panamensis) to assess how nutrient addition affected microbial enzyme activity and litter mass loss at the peat surface and at 50 cm depth. The second experiment tested the importance of HFA by reciprocal translocation of leaf litter from R. taedigera and C. panamensis forests, which differed in both litter chemistry and soil nutrient availability, to separate the influence of litter chemistry and soil/site properties on litter mass loss.

The activities of hydrolytic enzymes involved in the decomposition of large plant polymers were stimulated by nitrogen addition only where nitrogen availability was low relative to phosphorus, and were stimulated by phosphorus addition where phosphorus availability was low.

The addition of nitrogen, but not phosphorus, increased leaf litter decomposition under waterlogged conditions at 50 cm depth, but not at the peat surface.

Decomposition was greatest for autochthonous litter irrespective of site nutrient status, indicating that adaptation of the microbial community to low nutrients can partly overcome nutrient limitation, and suggesting that HFA can influence litter decomposition rates.

Synthesis. Our study shows that leaf litter decomposition and the activity of microbial enzymes in tropical peatlands are constrained in part by nutrient availability. However, such nutrient limitation of litter decomposition can be overcome by adaptation of the microbial community.