bluuebunny/crossref_metadata_2025_split huggingface dataset:
The inflammasome of circulatory collapse: single cell analysis of survival on extracorporeal life support
Authors: Kort Eric J. , Weiland Matthew , Grins Edgars , Eugster Emily , Milliron Hsiao-yun , Kelty Catherine , Shrestha Nabin Manandhar , Timek Tomasz , Leacche Marzia , Fitch Stephen J , Boeve Theodore J , Marco Greg , Dickinson Michael , Wilton Penny , Jovinge Stefan 
Published: March 2019

AbstractBackgroundDespite being a lifesaving intervention for the most critically ill and circulatory compromised patients, veno-arterial extra-corporeal life support (VA-ECLS) is associated with a mortality rate of nearly 60%. Understanding how the immune response to VA-ECLS either promotes or impedes survival would both enhance risk stratification and uncover new therapeutic strategies for these patients. However, conventional enumeration of peripheral blood mononuclear cells (PBMCs) and their subsets have failed to identify determinants of outcome among these cells.MethodsFlow cytometry and plasma cytokine measurement was combined with single cell RNASeq analysis of PBMCs from patients in circulatory shock being started on VA-ECLS to identify clinical, laboratory, and cellular features associated with 72 hour survival.ResultsNon-surviving patients exhibited higher plasma levels of the tissue aggressive inflammatory cytokines IL-1, IL-6, IL-12 and TNF-α. Distribution of cells between conventional PBMC subtypes was not predictive of survival. Single cell RNASeq analysis of discriminatory markers within each PBMC subtype revealed that the proportion of CD8+ Natural Killer T-cells (NKT) that expressed CD52, a known immune-modulator, was associated with improved survival. This cell population correlated inversely with IL-6 production. CD8+/CD52+ NKT cells were quantified by flow cytometry in a second, validation cohort. Those patients with a high proportion of CD52+ cells among all CD8+ NKT cells had more severe disease relative to the low CD52+ group, but nevertheless were nearly 5 time less likely to die in the first 72 hours of VA-ECLS (p=0.043 by log rank test).ConclusionsCD8+/CD52+ NKT cells are associated with survival in patients undergoing VA-ECLS. Fluidics based scRNASeq can reveal important aspects of pathophysiology in complex disease states such as circulatory collapse and VA-ECLS. Further studies in animal models will be required to determine if stimulation of CD8+/CD52+ NKT cell expansion may be an effective therapeutic strategy in this patient population.
In the chick embryo, estrogen can induce chromosomally male ZZ left gonad epithelial cells to form an ovarian cortex, which supports oogenesis
Authors: Guioli Silvana , Zhao Debiao , Nandi Sunil , Clinton Michael , Lovell-Badge Robin 
Published: March 2019

AbstractIn chickens, as in most amniotes, the first morphogenetic event in ovary differentiation is the formation of two distinct domains: a steroidogenic core, the medulla, overlain by the germ cell niche, the cortex. This process normally starts immediately after sex determination in the ZW embryos, substantially before the progression of germ cells into meiosis. In order to address the extent to which the cortical domain depends on intrinsic or extrinsic factors, we generated models of gonadal intersex by mixing ZW (female) and ZZ (male) cells in gonadal chimeras, or by altering estrogen levels of ZZ and ZW embryosin ovo. We found that both chomosomally female and male cells can be induced to form the cortical domain and that this can form relatively independently of the phenotypic sex of the medulla as long as estrogen is provided. We also show that the cortex promoting activity of estrogen signalling is mediated via Estrogen Receptor alpha within the left gonad epithelium. Therefore, either a ZW or ZZ cortical domain can provide an adequate niche to allow the germ cells to progress into meiosis. However, the presence of a medulla with an “intersex” or male phenotype may compromise this progression, causing cortical germ cells to remain in an immature state in the embryo.
Auditory sensory memory span for duration is severely curtailed in females with Rett Syndrome
Authors: Brima Tufikameni , Molholm Sophie , Molloy Ciara J. , Sysoeva Olga V. , Nicholas Eric , Djukic Aleksandra , Freedman Edward G. , Foxe John J. 
Published: March 2019

ABSTRACTRett syndrome (RTT), a rare neurodevelopmental disorder caused by mutations in the MECP2 gene, is typified by profound cognitive impairment and severe language impairment, rendering it very difficult to accurately measure auditory processing capabilities behaviorally in this population. Here we leverage the mismatch negativity (MMN) component of the event-related potential to measure the ability of RTT patients to decode and store occasional duration deviations in a stream of auditory stimuli. Sensory memory for duration, crucial for speech comprehension, has not been studied in RTT.High-density EEG was successfully recorded in 18 females with RTT and 27 age-matched typically developing (TD) controls (aged 6-22 years). Data from 7 RTT and 3 TD participants were excluded for excessive noise. Stimuli were 1kHz tones with a standard duration of 100ms and deviant duration of 180ms. To assess the sustainability of sensory memory, stimulus presentation rate was varied with stimulus onset asynchronies (SOAs) of 450, 900 and 1800ms. MMNs with maximum negativity over fronto-central scalp and a latency of 220-230ms were clearly evident for each presentation rate in the TD group, but only for the shortest SOA in the RTT group. Repeated-measures ANOVA revealed a significant group by SOA interaction. MMN amplitude correlated with age in the TD group only. MMN amplitude was not correlated with the Rett Syndrome Severity Scale. This study indicates that while RTT patients can decode deviations in auditory duration, the span of this sensory memory system is severely foreshortened, with likely implications for speech decoding abilities.
The restoration species pool for restoring tropical landscapes: assessment of the largest Brazilian supply chain
Authors: Vidal Cristina Yuri , Naves Rafaela Pereira , Viani Ricardo Augusto Gorne , Rodrigues Ricardo Ribeiro 
Published: March 2019

AbstractBrazil has been committed to fulfill international restoration goals and to enforce environmental legislation that will require private landowners to undertake ecological restoration of 21 million hectares of degraded and deforested landscapes. To support a broad range of restoration practices, a consolidated supply chain able to represent regional plant diversity is essential. This study investigated the restoration species pool in native plant nurseries in São Paulo state, southeastern Brazil and evaluated their geographic distribution, similarity of their plant stocks and the proportion of species represented from regional floras. Despite the lack of technical assistance and the large presence of non-native species (126 species, average 7.5 species/nursery), we found still more impressive native species richness in plant nurseries (561 species, average 86.4 species/nursery) from both the Atlantic Forest and Cerrado domains, representing 38 to 44% of regional floras. There was a huge bias toward tree and shrub species (96.6%) and absence or underrepresentation of other growth forms, as well as of savanna specialists, animal-dispersed and threatened species. The great dissimilarity of species offered in the nurseries surveyed underscores the importance of regional seed collection practices. Effective assistance and capacitation are essential to address issues related to misidentification of species, underrepresentation of most functional plant groups, and the presence of non-native species, as well as to support the supply chain, currently undergoing market downturn.Author contributions‘CYV and RRR conceived and designed the research. CYV performed data compilation; CYV and RPN analyzed the data; CYV and RAGV led the writing of the manuscript; all authors contributed to the drafts and gave final approval for publication.Implications for practicePlant nurseries collecting propagules from the surrounding vegetation provide an adequate – but limited – restoration species pool, with very dissimilar plant stocks available among plant nurseries.Plant nurseries concentrate their production on shrub and tree species and sub-represent other growth forms and some functional groups such as animal-dispersed and threatened species.The diversity of the restoration species pool is the basis to support a broad range of restoration practice, being essential to boost restoration initiatives that complement and support the conservation of remaining diversity in human modified landscapes.Effective assistance and capacity building should be provided to address issues related to misidentification, underrepresentation of functional groups and the presence of exotic and invasive species, as well as to support the supply chain, currently under market downturn
Interaction of Hippocampal Ripples and Cortical Slow Waves Leads to Coordinated Large-Scale Sleep Rhythm
Authors: Sanda Pavel , Malerba Paola , Jiang Xi , Krishnan Giri P. , Cash Sydney , Halgren Eric , Bazhenov Maxim 
Published: March 2019

AbstractThe dialogue between cortex and hippocampus is known to be crucial for sleep dependent consolidation of long lasting memories. During slow wave sleep memory replay depends on slow oscillation (SO) and spindles in the (neo)cortex and sharp wave-ripple complexes (SWR) in the hippocampus, however, the mechanisms underlying interaction of these rhythms are poorly understood. Here, we examined the interaction between cortical SOs and hippocampal SWRs in a computational model of the hippocampo-cortico-thalamic network and compared the results with human intracranial recordings during sleep. We observed that ripple occurrence peaked following the onset of SO (Down-to-Up-state transition) and that cortical input to hippocampus was crucial to maintain this relationship. Ripples influenced the spatiotemporal structure of cortical SO and duration of the Up/Down-states. In particular, ripples were capable of synchronizing Up-to-Down state transition events across the cortical network. Slow waves had a tendency to initiate at cortical locations receiving hippocampal ripples, and these “initiators” were able to influence sequential reactivation within cortical Up states. We concluded that during slow wave sleep, hippocampus and neocortex maintain a complex interaction, where SOs bias the onset of ripples, while ripples influence the spatiotemporal pattern of SOs.
α-integrins dictate distinct modes of type IV collagen recruitment to basement membranes
Authors: Jayadev Ranjay , Chi Qiuyi , Keeley Daniel P. , Hastie Eric L. , Sherwood David R. 
Published: March 2019

AbstractBasement membranes (BMs) are cell-associated extracellular matrices that support tissue integrity, signaling, and barrier properties. Type IV collagen is critical for BM mechanical and signaling functions, yet how it is directed into BMsin vivois unclear. Through live-cell imaging of endogenous localization, conditional knockdown, and misexpression experiments, we uncovered distinct mechanisms of integrin-mediated collagen recruitment toCaenorhabditis elegansgonadal and pharyngeal BMs. The putative laminin-binding αINA-1/βPAT-3 integrin was selectively activated in the gonad and recruited laminin, which directed moderate collagen incorporation. In contrast, the putative Arg-Gly-Asp (RGD)-binding αPAT-2/βPAT-3 integrin was activated in the pharynx and recruited high levels of collagen independent of laminin. Through an RNAi screen, we further identified the small GTPase RAP-3 (Rap1) as a pharyngeal-specific PAT-2/PAT-3 activator that modulates collagen levels. Together, these studies demonstrate that tissues can use distinct mechanisms to direct collagen incorporation into BMs to precisely control collagen levels and construct diverse BMs.
How to make more from exposure data? An integrated machine learning pipeline to predict pathogen exposure
Authors: Fountain-Jones Nicholas M. , Machado Gustavo , Carver Scott , Packer Craig , Recamonde-Mendoza Mariana , Craft Meggan E. 
Published: March 2019

AbstractPredicting infectious disease dynamics is a central challenge in disease ecology. Models that can assess which individuals are most at risk of being exposed to a pathogen not only provide valuable insights into disease transmission and dynamics but can also guide management interventions. Constructing such models for wild animal populations, however, is particularly challenging; often only serological data is available on a subset of individuals and non-linear relationships between variables are common.Here we take advantage of the latest advances in statistical machine learning to construct pathogen-risk models that automatically incorporate complex non-linear relationships with minimal statistical assumptions from ecological data with missing values. Our approach compares multiple machine learning algorithms in a unified environment to find the model with the best predictive performance and uses game theory to better interpret results. We apply this framework on two major pathogens that infect African lions: canine distemper virus (CDV) and feline parvovirus.Our modelling approach provided enhanced predictive performance compared to more traditional approaches, as well as new insights into disease risks in a wild population. We were able to efficiently capture and visualise strong non-linear patterns, as well as model complex interactions between variables in shaping exposure risk from CDV and feline parvovirus. For example, we found that lions were more likely to be exposed to CDV at a young age but only in low rainfall years.When combined with our data calibration approach, our framework helped us to answer questions about risk of pathogen exposure which are difficult to address with previous methods. Our framework not only has the potential to aid in predicting disease risk in animal populations, but also can be used to build robust predictive models suitable for other ecological applications such as modelling species distribution or diversity patterns.
Identification of Genes Regulating Cell Death inStaphylococcus aureus
Authors: Yee Rebecca , Feng Jie , Wang Jiou , Chen Jiazhen , Zhang Ying 
Published: March 2019

AbstractStaphylococcus aureusis an opportunistic pathogen that causes acute and chronic infections. Due toS. aureus’ s highly resistant and persistent nature, it is paramount to identify better drug targets in order to eradicateS. aureusinfections. Despite the efforts in understanding bacterial cell death, the genes and pathways ofS. aureuscell death remain elusive. Here, we performed a genome-wide screen using a transposon mutant library to study the genetic mechanisms involved inS. aureuscell death. Using a precisely controlled heat-ramp and acetic acid exposure assays, mutations in 27 core genes (hsdR1, hslO, nsaS, sspA, folD, mfd, vraF, kdpB, USA300HOU_2684, 0868, 0369, 0420, 1154, 0142, 0930, 2590, 0997, 2559, 0044, 2004, 1209, 0152, 2455, 0154, 2386, 0232, 0350 involved in transporters, transcription, metabolism, peptidases, kinases, transferases, SOS response, nucleic acid and protein synthesis) caused the bacteria to be more death-resistant. In addition, we identified mutations in core 10 genes (capA, gltT, mnhG1,USA300HOU_1780, 2496, 0200, 2029, 0336, 0329, 2386, involved in transporters, metabolism, transcription, cell wall synthesis) from heat-ramp and acetic acid that caused the bacteria to be more death-sensitive or with defect in persistence. Interestingly, death-resistant mutants were more virulent than the parental strain USA300 and caused increased mortality in aCaenorhabditis elegansinfection model. Conversely, death-sensitive mutants were less persistent and formed less persister cells upon exposure to different classes of antibiotics. These findings provide new insights into the mechanisms ofS. aureuscell death and offer new therapeutic targets for developing more effective treatments caused byS. aureus.
A topological data analysis based classification method for multiple measurements
Authors: Riihimäki Henri , Chachólski Wojciech , Theorell Jakob , Hillert Jan , Ramanujam Ryan 
Published: March 2019

AbstractBackgroundMachine learning models for repeated measurements are limited. Using topological data analysis (TDA), we present a classifier for repeated measurements which samples from the data space and builds a network graph based on the data topology. When applying this to two case studies, accuracy exceeds alternative models with additional benefits such as reporting data subsets with high purity along with feature values.ResultsFor 300 examples of 3 tree species, the accuracy reached 80% after 30 datapoints, which was improved to 90% after increased sampling to 400 datapoints. Using data from 100 examples of each of 6 point processes, the classifier achieved 96.8% accuracy. In both datasets, the TDA classifier outperformed an alternative model.ConclusionsThis algorithm and software can be beneficial for repeated measurement data common in biological sciences, as both an accurate classifier and a feature selection tool.
Back-propagation learning in deep Spike-By-Spike networks
Authors: Rotermund David , Pawelzik Klaus R. 
Published: March 2019

ABSTRACTNeural networks are important building blocks in technical applications. These artificial neural networks (ANNs) rely on noiseless continuous signals in stark contrast to the discrete action potentials stochastically exchanged among the neurons in real brains. A promising approach towards bridging this gap are the Spike-by-Spike (SbS) networks which represent a compromise between non-spiking and spiking versions of generative models that perform inference on their inputs. What is still missing are algorithms for finding weight sets that would optimize the output performances of deep SbS networks with many layers.Here, a learning rule for hierarchically organized SbS networks is derived. The properties of this approach are investigated and its functionality demonstrated by simulations. In particular, a Deep Convolutional SbS network for classifying handwritten digits (MNIST) is presented. When applied together with an optimizer this learning method achieves a classification performance of roughly 99.3% on the MNIST test data. Thereby it approaches the benchmark results of ANNs without extensive parameter optimization. We envision that with this learning rule SBS networks will provide a new basis for research in neuroscience and for technical applications, especially when they become implemented on specialized computational hardware.
Recommendations and guidelines for implementing PPP projects
Authors: Araujo Lissa Gomes , Piña Ana Beatriz Souza , Aidar Luiz Augusto Gimenez , Coelho Guilherme Oliveira , Carvalho Michele Tereza Marques 
Published: March 2019

Purpose
The purpose of this paper is to propose recommendations and guidelines for the initiation phase of a public–private partnership (PPP), focusing on the electricity sector in Brazil.

Design/methodology/approach
A literature review allowed gathering international best practices, while brainstorming meetings and document research permitted acquiring data from the Brazilian electricity sector through a multiple case study of 12 projects. By applying benchmarking principles to compare findings, the paper proposes guidelines and recommendations, which culminated in a final framework for implementing PPPs.

Findings
The created framework structures a series of recommendations with application in PPP projects. Also, the paper gathers worldwide best practices, which could increase the rate of success by avoiding problems throughout the other phases of a PPP project.

Research limitations/implications
This paper addresses the electricity sector. Due to the singularity of such infrastructure enterprises, it is possible that the framework suggested is not entirely applicable to other enterprises, being a suggestion for future studies to perform an adherent test. Also, validating this framework is not in the scope of this project.

Practical implications
The use of a framework on PPP implementations brings attention to necessary efforts on previous phases of projects, which can avoid financial and technical problems, improving the reliability of PPPs.

Originality/value
The application of guidelines and recommendations on the electricity sector has not appeared with such focus in previous studies. The paper provides a practical manner to upgrade the process and suggests a model for implementing PPPs.
Evaluation of PPP road projects in Greece
Authors: Marinelli Marina 
Published: March 2019

Purpose
The purpose of this paper is to explore and evaluate the problems encountered by five major road projects recently implemented in Greece as public–private partnerships (PPP) and make recommendations for improvement of the relevant managerial practices and contractual clauses for the benefit of similar future projects.

Design/methodology/approach
A qualitative approach was adopted in this research as only senior engineers with specific managerial experience were deemed suitable for the purposes of this research. In total, 15 semi-structured interviews were conducted with CEOs of the PPPs and heads of independent engineers involved in the projects’ implementation as well as with senior officials of two Greek Ministries.

Findings
The experts identified different areas of weakness relevant to the revenue risks, the planning of the scope, the management of designs and legal permits as well as the toll policy selected. They also made specific recommendations for the streamlining of the relevant procedures in the future.

Practical implications
The experts’ opinions and recommendations constitute a solid basis for the achievement of higher efficiency in the management of future PPP projects worldwide.

Originality/value
This research offers a holistic perspective to PPP project management as it sheds light to the problems encountered by the Greek PPP programme as a whole and incorporates the experience gained at the contracts’ renegotiation. The research draws from the experience of experts and offers recommendations for systemic improvements which can be widely applied in any geographical context.