bluuebunny/crossref_metadata_2025_split huggingface dataset:
Climate change negatively impacts dominant microbes in the sediments of a High Arctic lake
Authors: Colby Graham A. , Ruuskanen Matti O. , St. Pierre Kyra A. , St. Louis Vincent L. , Poulain Alexandre J. , Aris-Brosou Stéphane 
Published: July 2019

AbstractTemperatures in the Arctic are expected to increase dramatically over the next century, yet little is known about how microbial communities and their underlying metabolic processes will be affected by these environmental changes in freshwater sedimentary systems. To address this knowledge gap, we analyzed sediments from Lake Hazen, NU Canada. Here, we exploit the spatial heterogeneity created by varying runoff regimes across the watershed of this uniquely large lake at these latitudes to test how a transition from low to high runoff, used as one proxy for climate change, affects the community structure and functional potential of dominant microbes. Based on metagenomic analyses of lake sediments along these spatial gradients, we show that increasing runoff leads to a decrease in taxonomic and functional diversity of sediment microbes. Our findings are likely to apply to other, smaller, glacierized watersheds typical of polar or high latitude / high altitudes ecosystems; we can predict that such changes will have far reaching consequences on these ecosystems by affecting nutrient biogeochemical cycling, the direction and magnitude of which are yet to be determined.
Liver X Receptor activation regulates genes involved in lipid homeostasis in developing chondrocytes
Authors: Sun Margaret Man-Ger , Beier Frank 
Published: July 2019

AbstractObjectiveOsteoarthritis (OA) is the most common type of arthritis and causes debilitating symptoms and decreased quality of life. Currently available treatment options target symptoms but do not address the underlying issue of joint tissue degeneration. As such, a better understanding of the molecular mechanisms maintaining cartilage health is needed for developing novel therapeutic strategies. Liver X Receptors (LXRs) are nuclear receptors that have been previously shown to offer protection against OA. This is potentially due to suppression of chondrocyte hypertrophy in endochondral bone growth in response to LXR activation. In order to better understand the regulatory mechanisms behind this effect, we aimed to systematically examine LXR’s effects on growth plate chondrocyte gene expression.MethodsPrimary chondrocytes isolated from the long bones of E15.5 mice were treated with the specific LXR agonist, GW3965, and RNA was isolated for Affymetrix microarrays followed by real time qPCR validation. Bioinformatics analyses were performed using Gene Ontology (GO) and KEGG pathway analysis. Immunohistochemistry was conducted to examine protein localization of LXR and identified targets in GW3965-treated E15.5 tibiae compared to control.ResultsActivation of LXR in primary growth plate chondrocytes resulted in differential regulations of various genes involved in lipid metabolism, including several genes involved in cholesterol efflux. This pattern was compared to LXR activation in immature murine articular chondrocytes (IMACs), which revealed similar roles in lipid homeostasis. Immunohistochemical analysis of LXR and its identified targets Abca1 and Srebf1 revealed preferential protein localization to pre-hypertrophic and resting chondrocytes in GW3965-treated tibial growth plates compared to controls.ConclusionOur findings show for the first time that LXR activation alters expression of lipid metabolism genes in growth plate chondrocytes, in part through activation of molecules responsible for cellular cholesterol efflux. This provides insight into potential mechanisms through which LXR regulates cellular metabolism to alter chondrocyte behavior and phenotype.
Coalescent models at small effective population sizes and population declines are positively misleading
Authors: Lauterbur M. Elise 
Published: July 2019

AbstractPopulation genetics employs two major models for conceptualizing genetic relationships among individuals – outcome-driven (coalescent) and process-driven (forward). These models are complementary, but the basic Kingman coalescent and its extensions make fundamental assumptions to allow analytical approximations: a constant effective population size much larger than the sample size. These make the probability of multiple coalescent events per generation negligible. Although these assumptions are often violated in species of conservation concern, conservation genetics often uses coalescent models of effective population sizes and trajectories in endangered species. Despite this, the effect of very small effective population sizes, and their interaction with bottlenecks and sample sizes, on such analyses of genetic diversity remains unexplored. Here, I use simulations to analyze the influence of small effective population size, population decline, and their relationship with sample size, on coalescent-based estimates of genetic diversity. Compared to forward process-based estimates, coalescent models significantly overestimate genetic diversity in oversampled populations with very small effective sizes. When sampled soon after a decline, coalescent models overestimate genetic diversity in small populations regardless of sample size. Such overestimates artificially inflate estimates of both bottleneck and population split times. For conservation applications with small effective population sizes, forward simulations that do not make population size assumptions are computationally tractable and should be considered instead of coalescent-based models. These findings underscore the importance of the theoretical basis of analytical techniques as applied to conservation questions.
Network reaction norms: taking into account network position and network plasticity in response to environmental change
Authors: Bonnell Tyler R. , Vilette Chloé , Henzi S. Peter , Barrett Louise 
Published: July 2019

AbstractRecent studies have highlighted the link between consistent inter-individual differences in behaviour and consistency in social network position. There is also evidence that network structures can show temporal dynamics, suggesting that consistency in social network position across time does not preclude some form of plasticity in response to environmental variation. To better consider variation in network position and plasticity simultaneously we introduce the network reaction norm (NRN) approach. As an illustrative example, we used behavioural data on chacma baboons, collected over a period of seven years, to construct a time series of networks, using a moving window. Applying an NRN approach with these data, we found that most of the variation in network centrality could be explained by inter-individual differences in mean centrality. There was also evidence, however, for individual differences in network plasticity. These differences suggest that environmental conditions may influence which individuals are most central, i.e., they lead to an individual x environment interaction. We suggest that expanding from measures of repeatability in social networks to network reaction norms can provide a more temporally nuanced way to investigate social phenotypes within groups, and lead to a better understanding of the development and maintenance of individual variation in social behaviour.
Profiling the E. coli Membrane Interactome Captured in Peptidisc Libraries
Authors: Carlson Michael , Stacey R Greg , Young John , Wason Irvin , Zhao Zhiyu , Rattray David G , Scott Nichollas , Kerr Craig , Babu Mohan , Foster Leonard J. , Duong Franck 
Published: July 2019

ABSTRACTProtein-correlation-profiling (PCP), in combination with quantitative proteomics, has emerged as a high-throughput method for the rapid identification of dynamic protein complexes in native conditions. While PCP has been successfully applied to soluble proteomes, characterization of the membrane interactome has lagged, partly due to the necessary use of detergents to maintain protein solubility. Here, we apply the peptidisc, a ‘one-size fits all’ membrane mimetic, for the capture of the Escherichia coli cell envelope proteome and its high-resolution fractionation in the absence of detergent. Analysis of the SILAC-labeled peptidisc library via PCP allows generation of over 4900 possible binary interactions out of >700,000 random associations. Using well-characterized membrane protein systems such as the SecY translocon, the Bam complex and the MetNI transporter, we find our dataset very useful for identifying transient and surprisingly novel protein interactions. For example, we discover a trans-periplasmic super-complex comprising subunits of the Bam and Sec translocons, including membrane-bound chaperones YfgM and PpiD. We identify RcsF and OmpA as bone fide interactors of BamA, and we show that interaction of MetQ with the ABC transporter MetNI depends on its N-terminal lipid anchor. We also discover NlpA as a novel interactor of MetNIQ. Most of these interactions are largely undetected by standard detergent-based purification. Together, the peptidisc workflow applied to the proteomic field is emerging as a promising novel approach to characterize membrane protein interactions under native expression conditions and without genetic manipulation.
Population structure determined by comparative amplicon gene sequencing in biofilm and planktonic bacterial communities from pesticide-contaminated water
Authors: Lima Jhenifer Yonara , Moreira Cassiano , Costa Gessica , Freitas Paloma Nathane Nunes , Olchanheski Luiz Ricardo , Pileggi Sonia Alvim Veiga , Etto Rafael Mazer , Staley Christopher , Sadowski Michael Jay , Pileggi Marcos 
Published: July 2019

AbstractMolecular and bioinformatics tools for research are very important for biodiversity characterization in contaminated environments due the presence of a high percentage of nonculturable microorganisms. The wide use of pesticides in agriculture exposes microbiomes to stressful and selective conditions that demand survival strategies such as biofilm formation. The purpose of this work was to evaluate the bacterial population structure in planktonic and biofilm communities of water that was used for washing the packaging of herbicides and stored for six months in tanks. This substance is highly contaminated waste. Samples of water and biofilms from tanks and biofilms developed for short times in flasks were used for DNA isolation and 16S rRNA gene sequencing. The physicochemical conditions imposed by water used for washing the containers were inadequate for killing the bacterial genera identified according to water and wastewater standards. The variation in population structure and diversity was lower in the planktonic samples than in the biofilm samples, indicating a possible combination of genetic drift and subsequent selection of individuals surviving under stressful water conditions, such as heating and contact with agrochemicals, over a six-month period. The biofilm formation in water tanks contaminated with pesticides enabled the survival of bacterial genera harboring the essential processes for adaptation to these environments; the presence of these processes was determined according to descriptions obtained from the genomic databases. This study suggests the potential of bacterial genera identified in biofilms obtained from tanks to adapt to contaminated environments through their metabolic complexity. Thus, herbicide biodegradation kinetics can be accessed through a culturable collection obtained from these communities.
Ingestive behaviour of grazing ruminants: meta-analysis of the components linking bite mass to daily intake
Authors: Boval M. , Sauvant D. 
Published: July 2019

AbstractThis meta-analysis shed light on the quantitative adaptive responses of feeding behaviour of Cattle (C) and Small Ruminants (SR), facing variations of sward characteristics, notably of sward height (SH, 18. 7 ± 13.9 cm) and herbage bulk density (HBD, 1.73 ± 1.30 kg DM / m3). All responses expressed a plateau stressing an adaptive limit with extreme values of SH and HBD. The minimum plateau of BR (46.9 ± 14.6 min-1) is around 40 min-1, while IR values (different for C and SR, respectively 69.1 ± 38.1 vs. 99.9 ± 45.7 g/min/kg BW) ranged between a minimum and maximum plateau around 50 and 100 g/min/kg BW. Two other pasture management factors affect IR, namely forage allowance (10.16 ± 6.0, DM % BW) and daily proportion of time spent grazing (0.30 ± 0.08). The results obtained confirm the specifically key role of BM (1.80 ± 127 mg DM/kg BW) on IR. The regressions are IR=145 (1-exp (-b BM), b being equal respectively for C and SR and C to 0.44 vs. 0.54. This literature review has also revealed fundamental differences in behaviour between C and SR although no study to date has attempted to compare them simultaneously. SR have to chew more (2.7 ± 1.2 vs. 1.6 ± 0.5 JM/bite) to ingest the same amount of DM per bite than C, expressed in relation to BW, which allow them to ingest slightly quickly.ImplicationsThis article, following the previous one of Boval and Sauvant (2019), proposes a quantitative appraisal of the ingestive behaviour of grazing ruminants, based on studies published over 40 years, as well as well robust average values and relationships, considering inter- and intra-study effects and animal species specificities. This knowledge should contribute to a better overall understanding of the behavioural adaptation of ruminants at pasture, to the identification of key threshold values and appropriate parameters of interest to be considered, and to improve the efficiency and sensitivity of automatic devices, which are booming in the context of precision livestock farming at pasture.
Pathway-dependent regulation of sleep dynamics in a network model of the sleep-wake cycle
Authors: Héricé Charlotte , Sakata Shuzo 
Published: July 2019

AbstractSleep is a fundamental homeostatic process within the animal kingdom. Although various brain areas and cell types are involved in the regulation of the sleep-wake cycle, it is still unclear how different pathways between neural populations contribute to its regulation. Here we address this issue by investigating the behavior of a simplified network model upon synaptic weight manipulations. Our model consists of three neural populations connected by excitatory and inhibitory synapses. Activity in each population is described by a firing-rate model, which determines the state of the network. Namely wakefulness, rapid eye movement (REM) sleep or non-REM (NREM) sleep. By systematically manipulating the synaptic weight of every pathway, we show that even this simplified model exhibits non-trivial behaviors: for example, the wake-promoting population contributes not just to the induction and maintenance of wakefulness, but also to sleep induction. Although a recurrent excitatory connection of the REM-promoting population is essential for REM sleep genesis, this recurrent connection does not necessarily contribute to the maintenance of REM sleep. The duration of NREM sleep can be shortened or extended by changes in the synaptic strength of the pathways from the NREM-promoting population. In some cases, there is an optimal range of synaptic strengths that affect a particular state, implying that the amount of manipulations, not just direction (i.e., activation or inactivation), needs to be taken into account. These results demonstrate pathway-dependent regulation of sleep dynamics and highlight the importance of systems-level quantitative approaches for sleep-wake regulatory circuits.Author SummarySleep is essential and ubiquitous across animal species. Over the past half-century, various brain areas, cell types, neurotransmitters, and neuropeptides have been identified as part of a sleep-wake regulating circuitry in the brain. However, it is less explored how individual neural pathways contribute to the sleep-wake cycle. In the present study, we investigate the behavior of a computational model by altering the strength of connections between neuronal populations. This computational model is comprised of a simple network where three neuronal populations are connected together, and the activity of each population determines the current state of the model, that is, wakefulness, rapid-eye-movement (REM) sleep or non-REM (NREM) sleep. When we alter the connection strength of each pathway, we observe that the effect of such alterations on the sleep-wake cycle is highly pathway-dependent. Our results provide further insights into the mechanisms of sleep-wake regulation, and our computational approach can complement future biological experiments.
Forecasting type-specific seasonal influenza after 26 weeks in the United States using influenza activities in other countries
Authors: Choi S. B. , Kim J. , Ahn I. 
Published: July 2019

AbstractTo identify countries that have seasonal patterns similar to the time series of influenza surveillance data in the United States and other countries, and to forecast the 2018–2019 seasonal influenza outbreak in the U.S. using linear regression, auto regressive integrated moving average, and deep learning. We collected the surveillance data of 164 countries from 2010 to 2018 using the FluNet database. Data for influenza-like illness (ILI) in the U.S. were collected from the Fluview database. This cross-correlation study identified the time lag between the two time-series. Deep learning was performed to forecast ILI, total influenza, A, and B viruses after 26 weeks in the U.S. The seasonal influenza patterns in Australia and Chile showed a high correlation with those of the U.S. 22 weeks and 28 weeks earlier, respectively. The R2 score of DNN models for ILI for validation set in 2015–2019 was 0.722 despite how hard it is to forecast 26 weeks ahead. Our prediction models forecast that the ILI for the U.S. in 2018–2019 may be later and less severe than those in 2017–2018, judging from the influenza activity for Australia and Chile in 2018. It allows to estimate peak timing, peak intensity, and type-specific influenza activities for next season at 40th week. The correlation for seasonal influenza among Australia, Chile, and the U.S. could be used to decide on influenza vaccine strategy six months ahead in the U.S.
First Indian report on Genome-wide Comparison of Multidrug-ResistantEscherichia colifrom Blood Stream Infections
Authors: Devanga Ragupathi Naveen Kumar , Veeraraghavan Balaji , Muthuirulandi Sethuvel Dhiviya Prabaa , Anandan Shalini , Vasudevan Karthick , Neeravi Ayyan Raj , Kumar Daniel Jones Lionel , Sathyendra Sowmya , Iyadurai Ramya , Mutreja Ankur 
Published: July 2019

AbstractBackgroundMultidrug-resistant (MDR)E. coliwith extended-spectrum β-lactamases (ESBLs) is becoming endemic in health care settings around the world. Baseline data on virulence and AMR of specific lineages ofE. colicirculating in developing countries like India is currently lacking.MethodsWhole-genome sequencing was performed for 60 MDRE. coliisolates. Genome-wide analysis was performed at single nucleotide polymorphism (SNP) level resolution to identify the relation between the isolates in context of time, virulence and AMR determinants possessed.ResultsGenome comparison revealed the presence of ST-131 global MDR and ST410 as emerging-MDR clades ofE. coli. AMR gene profile for cephalosporin and carbapenem resistance differed between the clades. GenotypesblaCTX-M-15andblaNDM-5were common among cephalosporinases and carbapenemases, respectively. For aminoglycoside resistance,rmtBwas positive for 31.7% of the isolates, of which 30% were co-harboring carbapenemases. Further, the FimH types and virulence gene profile positively correlated with the SNP based phylogeny, which also revealed the evolution of MDR clones among the study population with temporal accumulation of SNPs. The predominant clone was ST167 (blaNDMlineage) followed by ST405 (global clone ST131 equivalent) and ST410 (fast spreading high risk clone).ConclusionsThis is the first report on the whole genome analysis of MDRE. colilineages circulating in India. Data from this study will provide public health agencies a baseline portfolio of AMR and virulence in pathogenicE. coliin the region.
Visualisation of ribosomes in Drosophila axons using Ribo-BiFC
Authors: Singh Anand K , Abdullahi Akilu , Soller Matthias , David Alexandre , Brogna Saverio 
Published: July 2019

AbstractRates of protein synthesis and the number of translating ribosomes vary greatly between different cells in various cell states. The distribution of assembled, and potentially translating, ribosomes within cells can be visualised in Drosophila by using Bimolecular Fluorescence Complementation (BiFC) to monitor the interaction between tagged pairs of 40S and 60S ribosomal proteins (RPs) that are close neighbours across inter-subunit junctions in the assembled 80S ribosome. Here we describe transgenes that express two novel RP pairs tagged with Venus-based BiFC fragments that considerably increase the sensitivity of this technique that we termed Ribo-BiFC. This improved method should provide a convenient way of monitoring the local distribution of ribosomes in most Drosophila cells and we suggest that could be implemented in other organisms. We visualized 80S ribosomes in larval photoreceptors and in other neurons. Assembled ribosomes are most abundant in the various neuronal cell bodies, but they are also present along the lengths of axons and are concentrated in growth cones of larval and pupal photoreceptors. Surprisingly, there is relatively less puromycin incorporation in the distal portion of axons in the optic stalk, suggesting that some of the ribosomes that have started translation may not be engaged in elongation in axons that are still growing.
The impact of CEO pay and its disclosure on stock price crash risk: evidence from China
Authors: Xu Jiahua , Zou Lan 
Published: July 2019

Purpose
The purpose of this paper is to investigate whether CEO pay is related to stock price crash risk, and how ownership concentration mediates this relationship.

Design/methodology/approach
The authors hypothesize that companies who disclose CEO pay would experience lower stock price crash risk than their non-transparent peers. For companies whose CEO pay is published, the authors conjecture that the CEO pay slice is positively related to stock price crash risk. The authors also investigate whether the impact of CEO pay on crash risk would be weaker or stronger under a concentrated ownership structure and a mutual fund ownership structure. This study relies on 14,499 firm-year observations from the Chinese capital market to shed light on these questions.

Findings
The authors demonstrate that the magnitude of CEO pay slice has little effect on stock price crash risk. However, whether CEO pay is disclosed at all is a strong indicator for stock price crash risk.

Originality/value
The paper expands on the literature by adding a new factor to explain the stock price crash risk, which is vital to investor protection and the stability of the financial market. The research also adds to the sparse literature on CEO centrality and has implications for corporate governance and public policy.