bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-proxy analyses of a mid-15th century ‘Middle Iron Age’ Bantu-speaker palaeo-faecal specimen elucidates the configuration of the ‘ancestral’ sub-Saharan African intestinal microbiome
Authors: Rifkin Riaan F. , Vikram Surendra , Ramond Jean-Baptiste , Rey-Iglesia Alba , Brand Tina B. , Porraz Guillaume , Val Aurore , Hall Grant , Woodborne Stephan , Bailly Matthieu Le , Potgieter Marnie , Underdown Simon J. , Koopman Jessica E. , Cowan Don A. , Van de Peer Yves , Willerslev Eske , Hansen Anders J. 
Published: October 2019

ABSTRACTThe archaeological incidence of ancient human faecal material provides a rare opportunity to explore the taxonomic composition and metabolic capacity of the ancestral human intestinal microbiome (IM). Following the recovery of a single desiccated palaeo-faecal specimen from Bushman Rock Shelter in Limpopo Province, South Africa, we applied a multi-proxy analytical protocol to the sample. Our results indicate that the distal IM of the Neolithic ‘Middle Iron Age’ (c. AD 1485) Bantu-speaking individual exhibits features indicative of a largely mixed forager-agro-pastoralist diet. Subsequent comparison with the IMs of the Tyrolean Iceman (Ötzi) and contemporary Hadza hunter-gatherers, Malawian agro-pastoralists and Italians, reveals that this IM precedes recent adaptation to ‘Western’ diets, including the consumption of coffee, tea, chocolate, citrus and soy, and the use of antibiotics, analgesics and also exposure to various toxic environmental pollutants. Our analyses reveal some of the causes and means by which current human IMs are likely to have responded to recent dietary changes, prescription medications and environmental pollutants, providing rare insight into human IM evolution following the advent of the Neolithic c. 12,000 years ago.
Evolution of CDK1 paralog specializations in a lineage with fast developing planktonic embryos
Authors: Ma Xiaofei , Øvrebø Jan Inge , Thompson Eric M 
Published: October 2019

AbstractThe active site of the essential, eukaryotic CDK1 kinase is generated by core structural elements, among which the PSTAIRE motif in the critical αC-helix, is universally conserved in metazoans. The CDK2 kinase, sharing the PSTAIRE, arose early in metazoan evolution and permitted subdivision of tasks along the S-M-phase axis. The marine chordate,Oikopleura dioica, is the only metazoan known to possess more than a single CDK1 ortholog, and all of its 5 paralogs show sequence divergences in the PSTAIRE. Through assessing CDK1 gene duplications in the appendicularian lineage, we show that the CDK1 activation loop substrate binding platform, ATP entrance site, hinge region, and main Cyclin binding interface, have all diversified under positive selection. Three of the 5 CDK1 paralogs are required for embryonic divisions and knockdown phenotypes illustrate further subdivision of functions along the S-M-phase axis. In parallel to CDK1 gene duplications, there has also been amplification in the Cyclin B complement. Among these, the CDK1d:Cyclin Ba pairing is required for oogenic meiosis and early embryogenesis and shows evidence of coevolution of an exclusive interaction. In an intriguing twist on the general rule that Cyclin B oscillations on a background of stable CDK1 levels regulate M-phase MPF activity, it is CDK1d protein levels that oscillate, rather than Cyclin Ba levels, to drive rapid, early embryonic cell cycles. Strikingly, the modified PSTAIRE of odCDK1d shows convergence over great evolutionary distance with plant CDKB, and in bothO. dioica, and plants, these variants exhibit increased specialization to M-phase.
Populations of genetic circuits are unable to find the fittest solution in a multilevel genotype-phenotype map
Authors: Catalán Pablo , Manrubia Susanna , Cuesta José A. 
Published: October 2019

AbstractThe evolution of gene regulatory networks (GRNs) is of great relevance for both evolutionary and synthetic biology. Understanding the relationship between GRN structure and its function can allow us to understand the selective pressures that have shaped a given circuit. This is especially relevant when considering spatiotemporal expression patterns, where GRN models have been shown to be extremely robust and evolvable. However, previous models that studied GRN evolution did not include the evolution of protein and genetic elements that underlie GRN architecture. Here we usetoyLIFE, a multilevel genotype-phenotype map, to show that not all GRNs are equally likely in genotype space and that evolution is biased to find the most common GRNs.toyLIFE rules create Boolean GRNs that, embedded in a one-dimensional tissue, develop a variety of spatiotemporal gene expression patterns. Populations oftoyLIFE organisms choose the most common GRN out of a set of equally fit alternatives and, most importantly, fail to find a target pattern when it is very rare in genotype space. Indeed, we show that the probability of finding the fittest phenotype increases dramatically with its abundance in genotype space. This phenotypic bias represents a mechanism that can prevent the fixation in the population of the fittest phenotype, one that is inherent to the structure of genotype space and the genotype-phenotype map.
Modeling the Shape of Synaptic Spines by their Actin Dynamics
Authors: Bonilla-Quintana Mayte , Wörgötter Florentin , Tetzlaff Christian , Fauth Michael 
Published: October 2019

AbstractDendritic spines are the morphological basis of excitatory synapses in the cortex and their size and shape correlates with functional synaptic properties. Recent experiments show that spines exhibit large shape fluctuations that are not related to activity-dependent plasticity but nonetheless might influence memory storage at their synapses. To investigate the determinants of such spontaneous fluctuations, we propose a mathematical model for the dynamics of the spine shape and analyze it in 2D — related to experimental microscopic imagery — and in 3D. We show that the spine shape is governed by a local imbalance between membrane tension and the expansive force from actin bundles that originates from discrete actin polymerization foci. Experiments have shown that only few such polymerization foci co-exist at any time in a spine, each having limited life time. The model shows that the momentarily existing set of such foci pushes the membrane along certain directions until foci are replaced and other directions may now be affected. We explore these relations in depth and use our model to predict shape and temporal characteristics of spines from the different biophysical parameters involved in actin polymerization. Reducing the model further to a single recursive equation we finally demonstrate that the temporal evolution of the number of active foci is sufficient to predict the size of the model-spines. Thus, our model provides the first platform to study the relation between molecular and morphological properties of the spine with a high degree of biophysical detail.Author summarySynaptic spines are post-synaptic contact points for pre-synaptic signals in many cortical neurons and it has been shown that synaptic transmission is correlated with spine size. However, spine size and shape can vary quite strongly on short time scales and it is currently unknown how these shape variations emerge. In this study we present a biophysical model that links spine shape fluctuations to the dynamics of the spine’s actin-based cytoskeleton. We show that shape fluctuations arise from the fact that fast actin polymerization in a spine is a discrete process happening at only few polymerization foci. Life and death of these foci determine from moment to moment how the membrane bulges or retracts. We provide an in-depth analysis of this effect for a large set of biophysical parameters and quantify the spatial-temporal structure of the spines. Our model, thus, provides a quantitative characterization of the link between spine morphology and the underlying molecular processes, which forms an essential step towards a better understanding of synaptic transmission during steady state but also during synaptic plasticity.
Effect of feedback regulation on stem cell fractions in tissues and tumors: understanding chemo-resistance in bladder cancer
Authors: Weiss Lora D. , van den Driessche P. , Lowengrub John S. , Wodarz Dominik , Komarova Natalia L. 
Published: October 2019

AbstractWhile resistance mutations are often implicated in the failure of cancer therapy, lack of response also occurs without such mutants. In bladder cancer mouse xenografts, repeated chemotherapy cycles have resulted in cancer stem cell (CSC) enrichment, and consequent loss of therapy response due to the reduced susceptibility of CSCs to drugs. A particular feedback loop present in the xenografts has been shown to promote CSC enrichment in this system. Yet, many other regulatory loops might also be operational and might promote CSC enrichment. Their identification is central to improving therapy response. Here, we perform a comprehensive mathematical analysis to define what types of regulatory feedback loops can and cannot contribute to CSC enrichment, providing guidance to the experimental identification of feedback molecules. We derive a formula that reveals whether or not the cell population experiences CSC enrichment over time, based on the properties of the feedback. We find that negative feedback on the CSC division rate or positive feedback on differentiated cell death rate can lead to CSC enrichment. Further, the feedback mediators that achieve CSC enrichment can be secreted by either CSCs or by more differentiated cells. The extent of enrichment is determined by the CSC death rate, the CSC self-renewal probability, and by feedback strength. Defining these general characteristics of feedback loops can guide the experimental screening for and identification of feedback mediators that can promote CSC enrichment in bladder cancer and potentially other tumors. This can help understand and overcome the phenomenon of CSC-based therapy resistance.
Eco-evolutionary dynamics of Plasmodium genotypes under mass drug administration
Authors: Bargués-Ribera Maria , Reeves R. Guy , Gokhale Chaitanya S. 
Published: October 2019

AbstractMass Drug Administration (MDA) is regarded as a potential strategy for locally interrupting transmission of human malaria under specific circumstances. However, insights on how MDA affects the eco-evolutionary dynamics of different Plasmodium species are not well known. We provide a computational model where the ecologically explicit life cycle of the parasite is implemented. Since the parasite inhabits two different ecological niches – human host and the mosquito – it undergoes different selection pressures during its reproduction. We use the model to perform an evolutionary analysis of the dynamics of resistance alleles under atovaquone, chloroquine and combined atovaquone-chloroquine drug treatments. Our study shows how the reduced viability of resistant parasites in the mosquito affects the spread of resistance and transmission interruption in treated human populations. Overall, results confirm that the disadvantage of drug-resistant genotypes in the mosquito vector is a good tool to achieve malaria control goals under MDA programmes.Author summaryEvery year there are millions of new malaria cases reported worldwide. The cause of the disease is the infection by Plasmodium, a protozoan which is transmitted between humans through the bite of a mosquito. Antimalarials have existed since long, but Plasmodium has evolved resistance to the treatment, making it necessary to develop new strategies to heal the infected humans. Lately, it has been pointed out that mosquitoes could be our allies when using drugs such as atovaquone, which resistant parasites have difficulties to reproduce in the mosquito. Here we study the scenarios in which these drugs, used in Mass Drug Administration (MDA) programmes, can interrupt the transmission of malaria in local treated populations.
Sensitivity and uncertainty analysis of two human atrial cardiac cell models using Gaussian process emulators
Authors: Coveney Sam , Clayton Richard H. 
Published: October 2019

AbstractCardiac cell models reconstruct the action potential and calcium dynamics of cardiac myocytes, and are becoming widely used research tools. These models are highly detailed, with many parameters in the equations that describe current flow through ion channels, pumps, and exchangers in the cell membrane, and so it is difficult to link changes in model inputs to model behaviours. The aim of the present study was to undertake sensitivity and uncertainty analysis of two models of the human atrial action potential. We used Gaussian processes to emulate the way that 11 features of the action potential and calcium transient produced by each model depended on a set of. The emulators were trained by maximising likelihood conditional on a set of design data, obtained from 300 model evaluations. For each model evaluation, the set of inputs was obtained from uniform distributions centred on the default values for each parameter, using latin-hypercube sampling. First order and total effect sensitivity indices were calculated for each combination of input and output. First order indices were well correlated with the square root of sensitivity indices obtained by partial least squares regression of the design data. The sensitivity indices highlighted a difference in the balance of inward and outward currents during the plateau phase of the action potential in each model, with the consequence that changes to one parameter can have opposite effects in the two models. Overall the interactions among inputs were not as important as the first order effects, indicating that model parameters tend to have independent effects on the model outputs. This study has shown that Gaussian process emulators are an effective tool for sensitivity and uncertainty analysis of cardiac cell models.Author summaryThe time course of the cardiac action potential is determined by the balance of inward and outward currents across the cell membrane, and these in turn depend on dynamic behaviour of ion channels, pumps and exchangers in the cell membrane. Cardiac cell models reconstruct the action potential by representing transmembrane current as a set of stiff and nonlinear ordinary differential equations. These models capture biophysical detail, but are complex and have large numbers of parameters, so cause and effect relationships are difficult to identify. In recent years there has been an increasing interest in uncertainty and variability in computational models, and a number of tools have been developed. In this study we have used one of these tools, Gaussian process emulators, to compare and contrast two models of the human atrial action potential. We obtained sensitivity indices based on the proportion of variance in a model output that is accounted for by variance in each of the model parameters. These sensitivity indices highlighted the model parameters that had the most influence on the model outputs, and provided a means to make a quantitative comparison between the models.
CNLLRR: A Novel Low-Rank Representation Method for Single-cell RNA-seq Data Analysis
Authors: Yu Na , Liu Jin-Xing , Gao Ying-Lian , Zheng Chun-Hou , Shang Junliang , Cai Hongmin 
Published: October 2019

AbstractThe development of single-cell RNA-sequencing (scRNA-seq) technology has enabled the measurement of gene expression in individual cells. This provides an unprecedented opportunity to explore the biological mechanisms at the cellular level. However, existing scRNA-seq analysis methods are susceptible to noise and outliers or ignore the manifold structure inherent in the data. In this paper, a novel method called Cauchy non-negative Laplacian regularized low-rank representation (CNLLRR) is proposed to alleviate the above problem. Specifically, we employ the Cauchy loss function (CLF) instead of the conventional norm constraints in the noise matrix of CNLLRR, which will enhance the robustness of the method. In addition, graph regularization term is applied to the objective function, which can capture the paired geometric relationships between cells. Then, alternating direction method of multipliers (ADMM) is adopted to solve the optimization problem of CNLLRR. Finally, extensive experiments on scRNA-seq data reveal that the proposed CNLLRR method outperforms other state-of-the-art methods for cell clustering, cell visualization and prioritization of gene markers. CNLLRR contributes to understand the heterogeneity between cell populations in complex biological systems.Author summaryAnalysis of single-cell data can help to further study the heterogeneity and complexity of cell populations. The current analysis methods are mainly to learn the similarity between cells and cells. Then they use the clustering algorithm to perform cell clustering or downstream analysis on the obtained similarity matrix. Therefore, constructing accurate cell-to-cell similarity is crucial for single-cell data analysis. In this paper, we design a novel Cauchy non-negative Laplacian regularized low-rank representation (CNLLRR) method to get a better similarity matrix. Specifically, Cauchy loss function (CLF) constraint is applied to punish noise matrix, which will improve the robustness of CNLLRR to noise and outliers. Moreover, graph regularization term is applied to the objective function, which will effectively encode the local manifold information of the data. Further, these will guarantee the quality of the cell-to-cell similarity matrix learned. Finally, single-cell data analysis experiments show that our method is superior to other representative methods.
Immunoglobulin profile and B-cell frequencies are altered with changes in the cellular micro-environment independent of the stimulation conditions
Authors: Moore Dannielle K , Leisching Gina R , Snyders Candice I , Gutschmidt Andrea , van Rensburg Ilana C , Loxton Andre G ,   the SU-IRG Consortium
Published: October 2019

AbstractB-cells are essential in the defense againstMycobacterium tuberculosis. Studies on isolated cells may not accurately reflect the responses that occurin vivodue to the presence of other cells. This study elucidated the influence of microenvironment complexity on B-cell polarisation and function in the context of TB disease. B-cell function was tested in whole blood, PBMC’s and as isolated cells. The different fractions were stimulated and the B-cell phenotype and immunoglobulin profiles analysed. The immunoglobulin profile and killer B-cell frequencies varied for each of the investigated sample types, while in an isolated cellular environment, secretion of immunoglobulin isotypes IgA, IgG2 and IgG3 was hampered. The differences in the immunoglobulin profile highlight the importance of cell-cell communication for B-cell activation. In contrast, increased frequencies of killer B-cells were observed following cellular isolation, suggesting a biased shift in augmented immune responsein vitro. This suggests that humoral B-cell function and development was impaired likely due to a lack of co-stimulatory signals from other cell types. Thus, B-cell function should ideally be studied in a PBMC or whole blood fraction.
Maize nested introgression library provides evidence for the involvement ofliguleless1in resistance to northern leaf blight
Authors: Kolkman Judith M. , Strable Josh , Harline Kate , Kroon Dallas E. , Wiesner-Hanks Tyr , Bradbury Peter J. , Nelson Rebecca J. 
Published: October 2019

AbstractPlant disease resistance is largely governed by complex genetic architecture. In maize, few disease resistance loci have been characterized. Near-isogenic lines (NILs) are a powerful genetic tool to dissect quantitative trait loci (QTL). We analyzed an introgression library of maize near-isogenic lines (NILs), termed a nested NIL (nNIL) library for resistance to northern leaf blight (NLB) caused by the fungal pathogenSetosphaeria turcica. The nNIL library was comprised of 412 BC5F4NILs that originated from 18 diverse donor parents and a common recurrent parent, B73. Single nucleotide polymorphisms identified through genotyping by sequencing (GBS) were used to define introgressions and for association analysis. NILs that conferred resistance and susceptibility to NLB were comprised of introgressions that overlapped known NLB QTL. Genome-wide association analysis and stepwise regression further resolved five QTL regions, and implicated several candidate genes, includingLiguleless1(Lg1), a key determinant of leaf architecture in cereals. Two independently-derived mutant alleles oflg1inoculated withS. turcicashowed enhanced susceptibility to NLB. In the maize nested association mapping population, leaf angle was positively correlated with NLB in five recombinant inbred line (RIL) populations, and negatively correlated with NLB in four RIL populations. This study demonstrates the power of a nNIL library combined with high density SNP coverage to resolve QTLs. Furthermore, the role oflg1in leaf architecture and in resistance to NLB has important applications in crop improvement.Significance Statement (120 words)Understanding the genetic basis of disease resistance is important for crop improvement. We analyzed response to northern leaf blight (NLB) in a maize population consisting of 412 near-isogenic lines (NILs) derived from 18 diverse donor parents backcrossed to a recurrent parent, B73. NILs were genotyped by sequencing to detect introgressed segments. We identified NILs with greater resistance or susceptibility to NLB than B73. Genome-wide association analysis, coupled with stepwise regression, identified 5 candidate loci for NLB resistance, including theliguleless1gene. The LIGULELESS1 transcription factor is critical in development of the leaf ligular region and influences leaf angle. We found thatliguleless1mutants are significantly more susceptible to NLB, uncovering a pleiotropic role forliguleless1in development and disease resistance.
Governmentality and performance for the smart city
Authors: Argento Daniela , Grossi Giuseppe , Jääskeläinen Aki , Servalli Stefania , Suomala Petri 
Published: October 2019

Purpose
The purpose of this paper is to explore the role of performance measurement systems as technologies of government in the operationalisation of smart city programmes. It answers the research question: how do the development and use of performance measurement systems support smart cities in the achievement of their goals?

Design/methodology/approach
This paper presents a longitudinal case study that uses an interventionist approach to investigate the possibilities and limitations of the use of performance measurement systems as technologies of government in a smart city. Interpretations are theoretically informed by the Foucauldian governmentality framework (Foucault, 2009) and by public sector performance measurement literature.

Findings
The findings address the benefits and criticalities confronting a smart city that introduces new performance measurement systems as a technology of government. Such technologies become problematic tools when the city network is characterised by a fragmentation of inter-departmental processes, and when forms of resistance emerge due to a lack of process owners, horizontal accountability and cooperation among involved parties.

Research limitations/implications
This paper is based on a case study of a single smart city, and outlines the need for both comparative and multidisciplinary analyses in order to analyse the causes and effects of smart city challenges.

Originality/value
This paper offers a critical understanding of the role of accounting in the smart city. The ineffectiveness of performance measurement systems is related to the multiple roles of such technologies of government, which may lead to a temporary paralysis in the achievement of smart city goals and programmes.