bluuebunny/crossref_metadata_2025_split huggingface dataset:
EVOLUTIONARY TRENDS IN SPECIES COMPLEX DIAGNOSED BY CYTOGENETIC POLYMORPHISM: THE CASE OFHypostomus ancistroides(SILURIFORMES, LORICARIIDAE)
Authors: Rocha-Reis Dinaíza Abadia , Brandão Karina de Oliveira , dos Santos Dergam Jorge Abdala , Pasa Rubens , Kavalco Karine Frehner 
Published: September 2020

ABSTRACTHypostominae is a subfamily of Loricariidae with great variation in color characters and external morphology. The genusHypostomuspresents the largest number of species ever karyotyped, withHypostomus ancistroidescharacterized as a group of cryptic species. In the 15 natural populations ofH. ancistroidesstudied, there are 15 different karyomorphs, with variations in diploid number, sex chromosome systems, and markers, such as C-banding and location of ribosomal cistrons. The objective of this work was to present molecular and chromosomal data of four new populations ofHypostomus ancistroidesand to discuss the observed evolutionary trends for this group of a cryptic complex of species. We analyzed specimens from four sampling points in the Tietê, Mogi-Guaçu, and Grande river basins, all in the state of São Paulo, southeastern Brazil. We performed techniques such as the detection of constitutive heterochromatin and ribosomal sites (5S and 18S), in addition to phylogenetic analyses. All specimens presented 2n=68 chromosomes without supernumerary elements or sex-related heteromorphisms. However, each population has a different karyotype with unique characteristics. The different karyomorphs are a consequence of the presence of Robertsonian rearrangements, such as centric fissions and pericentric inversions, which play an important role in the evolution of Hypostominae. Although variable in relation to the location of constitutive heterochromatin, we observed the presence of banding C in some chromosomes of all karyomorphs, which may indicate the existence of some homology. Another conservative feature is the presence of two pairs of subtelocentric or acrocentric chromosomes carrying 18S rDNA cistrons in the terminal region of the chromosomes. However, we observed the discontinuity of cytogenetic and phylogenetic data, with the formation of different groups (Araras + Indaiatuba and Botucatu + Terra Roxa in cytogenetics, in contrast to Araras + Terra Roxa and Botucatu and Indaiatuba in the phylogeny), suggesting that several derived karyomorphs may be produced from a pluripotent karyomorph as a result of the intrinsic plasticity of the species karyotype. Thus, each new arrangement would be independent in the forms analyzed, as they do not seem to be lineages from the same direct ancestor. Given the above, we believe that the genusHypostomuscontinues to be one of the most diverse among the Siluriformes, however, we began to understand a little more about the karyotypic diversity of the group by associating different approaches, such as phylogenetic analyses.
A synergistic core for human brain evolution and cognition
Authors: Luppi Andrea I. , Mediano Pedro A.M. , Rosas Fernando E. , Holland Negin , Fryer Tim D. , O’Brien John T. , Rowe James B. , Menon David K. , Bor Daniel , Stamatakis Emmanuel A. 
Published: September 2020

AbstractA fundamental question in neuroscience is how brain organisation gives rise to humans’ unique cognitive abilities. Although complex cognition is widely assumed to rely on frontal and parietal brain regions, the underlying mechanisms remain elusive: current approaches are unable to disentangle different forms of information processing in the brain. Here, we introduce a powerful framework to identify synergistic and redundant contributions to neural information processing and cognition. Leveraging multimodal data including functional MRI, PET, cytoarchitectonics and genetics, we reveal that synergistic interactions are the fundamental drivers of complex human cognition. Whereas redundant information dominates sensorimotor areas, synergistic activity is closely associated with the brain’s prefrontal-parietal and default networks; furthermore, meta-analytic results demonstrate a close relationship between high-level cognitive tasks and synergistic information. From an evolutionary perspective, the human brain exhibits higher prevalence of synergistic information than non-human primates. At the macroscale, we demonstrate that high-synergy regions underwent the highest degree of evolutionary cortical expansion. At the microscale, human-accelerated genes promote synergistic interactions by enhancing synaptic transmission. These convergent results provide critical insights that synergistic neural interactions underlie the evolution and functioning of humans’ sophisticated cognitive abilities, and demonstrate the power of our widely applicable information decomposition framework.
INTEGRINS MEDIATE PLACENTAL EXTRACELLULAR VESICLE TRAFFICKING TO LUNG AND LIVER IN VIVO
Authors: Nguyen Sean L. , Ahn Soo Hyun , Greenberg Jacob W. , Collaer Benjamin W. , Agnew Dalen W. , Arora Ripla , Petroff Margaret G. 
Published: September 2020

ABSTRACTMembrane-bound extracellular vesicles (EVs) mediate intercellular communication in all organisms, and those produced by placental mammals have become increasingly recognized as significant mediators of fetal-maternal communication. Here, we aimed to identify maternal cells targeted by placental EVs and elucidate the mechanisms by which they traffic to these cells. Exogenously administered pregnancy-associated EVs traffic specifically to the lung; further, placental EVs associate with lung interstitial macrophages and liver Kupffer cells in an integrin-dependent manner. Localization of EV to maternal lungs was confirmed in unmanipulated pregnancy using a transgenic reporter mouse model, which also provided in situ and in vitro evidence that fetally-derived EVs, rarely, may cause genetic alteration of maternal cells. These results provide for the first time direct in vivo evidence for targeting of placental EVs to maternal immune cells, and further, evidence that EVs can alter cellular phenotype.
DNA nanoswitch barcodes for multiplexed biomarker profiling
Authors: Chandrasekaran Arun Richard , MacIsaac Molly , Vilcapoma Javier , Hansen Clinton H. , Yang Darren , Wong Wesley P. , Halvorsen Ken 
Published: September 2020

ABSTRACTThe detection of molecular biomarkers plays a key role in the clinic, aiding in diagnostics and prognostics, and in the research laboratory, contributing to our basic understanding of diseases. The ability to detect multiple and diverse molecular biomarkers within a single accessible assay would have great utility, providing a more comprehensive picture for clinical evaluation and research, but is a challenge with standard methods. One promising approach is the use of dynamic DNA nanostructures that can respond to molecular biomarkers, which have recently been used in a variety of biosensing strategies. In this work, we report the use of programmable DNA nanoswitches for the multiplexed detection of up to 6 biomarkers within a single pot through the use of a barcoded gel-based readout. We demonstrate the barcoding capability using gene fragments that correspond to 6 different diseases, with each fragment or combination of fragments producing a unique barcode signature. As a defining feature of our method, we show “mixed multiplexing” for simultaneous barcoded detection of different types of biomolecules – DNA, RNA, antibody and protein in a single assay. To demonstrate clinical potential, we show multiplexed detection of a prostate cancer biomarker panel in serum that includes two microRNA sequences and prostate specific antigen (PSA). This strategy holds promise in clinical diagnostics for profiling complex and diverse biomarker panels.
Mechanical Work Accounts for Most of the Energetic Cost in Human Running
Authors: Riddick RC , Kuo AD 
Published: September 2020

AbstractThe metabolic cost of human running is challenging to explain, in part because direct measurements of muscles are limited in availability. Active muscle work costs substantial energy, but series elastic tissues such as tendon may also perform work while muscles contract isometrically at a lower cost. While it is unclear to what extent muscle vs. series elastic work occurs, there are indirect data that can help resolve their relative contributions to the cost of running. We therefore developed a simple cost estimate for muscle work in humans running (N = 8) at moderate speeds based on measured joint energetics. We found that even if 50% of the work observed at the joints is performed passively, active muscle work still accounts for 76% of the net energetic cost. Up to 24% of this cost due is required to compensate for dissipation from soft tissue deformations. The cost of active work may be further adjusted based on assumptions of multi-articular energy transfer and passive elasticity, but even the most conservative assumptions yield active work costs of at least 60%. Passive elasticity can greatly reduce the active work of running, but muscle work still explains most of the overall energetic cost.
SSMD: A semi-supervised approach for a robust cell type identification and deconvolution of mouse transcriptomics data
Authors: Lu Xiaoyu , Tu Szu-Wei , Chang Wennan , Wan Changlin , Wang Jiashi , Zang Yong , Ramdas Baskar , Kapur Reuben , Lu Xiongbin , Cao Sha , Zhang Chi 
Published: September 2020

ABSTRACTDeconvolution of mouse transcriptomic data is challenged by the fact that mouse models carry various genetic and physiological perturbations, making it questionable to assume fixed cell types and cell type marker genes for different dataset scenarios. We developed aSemi-SupervisedMouse dataDeconvolution (SSMD) method to study the mouse tissue microenvironment (TME). SSMD is featured by (i) a novel non-parametric method to discover data set specific cell type signature genes; (ii) a community detection approach for fixing cell types and their marker genes; (iii) a constrained matrix decomposition method to solve cell type relative proportions that is robust to diverse experimental platforms. In summary, SSMD addressed several key challenges in the deconvolution of mouse tissue data, including: (1) varied cell types and marker genes caused by highly divergent genotypic and phenotypic conditions of mouse experiment, (2) diverse experimental platforms of mouse transcriptomics data, (3) small sample size and limited training data source, and (4) capable to estimate the proportion of 35 cell types in blood, inflammatory, central nervous or hematopoietic systems. In silico and experimental validation of SSMD demonstrated its high sensitivity and accuracy in identifying (sub) cell types and predicting cell proportions comparing to state-of-the-arts methods. A user-friendly R package and a web server of SSMD are released viahttps://github.com/xiaoyulu95/SSMD.Key pointsWe provide a novel tissue deconvolution method, namely SSMD, which is specifically designed for mouse data to handle the variations caused by different mouse strain, genetic and phenotypic background, and experimental platforms.SSMD is capable to detect data set and tissue microenvironment specific cell markers for more than 30 cell types in mouse blood, inflammatory tissue, cancer, and central nervous system.SSMD achieve much improved performance in estimating relative proportion of the cell types compared with state-of-the-art methods.The semi-supervised setting enables the application of SSMD on transcriptomics, DNA methylation and ATAC-seq data.A user friendly R package and a R shiny of SSMD based webserver are also developed.
Outer membrane lipoprotein DolP interacts with the BAM complex and promotes fitness during envelope stress response
Authors: Ranava David , Yang Yiying , Orenday-Tapia Luis , Rousset François , Turlan Catherine , Cui Lun , Morales Violette , Moulin Cyril , Munoz Gladys , Rech Jérôme , Caumont-Sarcos Anne , Albenne Cécile , Bikard David , Ieva Raffaele 
Published: September 2020

AbstractIn Gram-negative bacteria, coordinated remodelling of the outer membrane (OM) and the peptidoglycan is crucial for envelope integrity. Envelope stress caused by unfolded OM proteins (OMPs) activates sigmaE (σE) in Enterobacteria. σEupregulates OMP biogenesis factors, including the β-barrel assembly machinery (BAM) that catalyzes OMP-folding. Elevated σEactivity, however, can be detrimental for OM integrity. Here we report that DolP (YraP), a σE-upregulated OM lipoprotein important for envelope integrity, is a novel interactor of BAM and we demonstrate that OM-assembled BamA is a critical determinant of the BAM-DolP complex. Mid-cell recruitment of DolP had been previously associated to activation of septal peptidoglycan remodelling during cell division, but its role during envelope stress was unknown. We now show that DolP promotes cell fitness upon stress-induced activation of σEand opposes a detrimental effect caused by the overaccumulation of BAM in the OM. During envelope stress, DolP loses its association with the mid-cell, thus suggesting a possible link between envelope stress caused by impaired OMP biogenesis and the regulation of a late step of cell division.
Predicting species and community responses to global change in Australian mountain ecosystems using structured expert judgement
Authors: Camac James S. , Umbers Kate D.L. , Morgan John W. , Geange Sonya R. , Hanea Anca , Slatyer Rachel A. , McDougall Keith L. , Venn Susanna E. , Vesk Peter A. , Hoffmann Ary A. , Nicotra Adrienne B. 
Published: September 2020

AbstractConservation managers are under increasing pressure to make decisions about the allocation of finite resources to protect biodiversity under a changing climate. However, the impacts of climate and global change drivers on species are outpacing our capacity to collect the empirical data necessary to inform these decisions. This is particularly the case in the Australian Alps which has already undergone recent changes in climate and experienced more frequent large-scale bushfires. In lieu of empirical data, we used a structured expert elicitation method (the IDEA protocol) to estimate the abundance and distribution of nine vegetation groups and 89 Australian alpine and subalpine species by the year 2050. Experts predicted that most alpine vegetation communities would decline in extent by 2050; only woodlands and heathlands were predicted to increase in extent. Predicted species-level responses for alpine plants and animals were highly variable and uncertain. In general, alpine plants spanned the range of possible responses, with some expected to increase, decrease or not change in cover. By contrast, almost all animal species were predicted to decline or not change in abundance or elevation range; more species with water-centric life-cycles were expected to decline in abundance than other species. In the face of rapid change and a paucity of data, the method and outcomes outlined here provide a pragmatic and coherent basis upon which to start informing conservation policy and management, although this approach does not diminish the importance of collecting long-term ecological data.Article Impact StatementExpert knowledge is used to quantify the adaptive capacity and thus, the risk posed by global change, to Australian mountain flora and fauna.
Mechano-chemical feedback leads to competition for BMP signalling during pattern formation
Authors: Toddie-Moore Daniel J. , Montanari Martti P. , Tran Ngan Vi , Brik Evgeniy M. , Antson Hanna , Salazar-Ciudad Isaac , Shimmi Osamu 
Published: September 2020

AbstractDevelopmental patterning is thought to be regulated by conserved signalling pathways. Initial patterns are often broad before refining to only those cells that commit to a particular fate. However, the mechanisms by which pattern refinement takes place remain to be addressed. Using the posterior crossvein (PCV) of theDrosophilapupal wing as a model, into which bone morphogenetic protein (BMP) ligand is extracellularly transported to instruct vein patterning, we investigate how pattern refinement is regulated. We found that BMP signalling induces apical enrichment of Myosin II in developing crossvein cells to regulate apical constriction. Live imaging of cellular behaviour indicates that changes in cell shape are dynamic and transient, only being maintained in those cells that retain vein fate after refinement. Disrupting cell shape changes throughout the PCV inhibits pattern refinement. In contrast, disrupting cell shape in only a subset of vein cells can result in a loss of BMP signalling. In addition, we observed that expressing the constitutively active form of the BMP type I receptor in clones caused apical constriction autonomously and often induced BMP signalling loss in the PCV region in a non-autonomous manner. We propose that the cell shape changes of future PCV cells allow them to compete more efficiently for the basally localised BMP signal by forming a mechano-chemical feedback loop. This study highlights a new form of competition among the cells: competing for a signal that induces cell fate.
A modified boosted support vector machine to rate banks
Authors: Viswanathan Hari Hara Krishna Kumar , Murugesan Punniyamoorthy , Rengasamy Sundar , Vilvanathan Lavanya 
Published: September 2020

PurposeThe purpose of this study is to compare the classification learning ability of our algorithm based on boosted support vector machine (B-SVM), against other classification techniques in predicting the credit ratings of banks. The key feature of this study is the usage of an imbalanced dataset (in the response variable/rating) with a smaller number of observations (number of banks).Design/methodology/approachIn general, datasets in banking sector are small and imbalanced too. In this study, 23 Scheduled Commercial Banks (SCBs) have been chosen (in India), and their corresponding corporate ratings have been collated from the Indian subsidiary of reputed global rating agency. The top management of the rating agency provided 12 input (quantitative) variables that are considered essential for rating a bank within India. In order to overcome the challenge of dataset being imbalanced and having small number of observations, this study uses an algorithm, namely “Modified Boosted Support Vector Machines” (MBSVMs) proposed by Punniyamoorthy Murugesan and Sundar Rengasamy. This study also compares the classification ability of the aforementioned algorithm against other classification techniques such as multi-class SVM, back propagation neural networks, multi-class linear discriminant analysis (LDA) and k-nearest neighbors (k-NN) classification, on the basis of geometric mean (GM).FindingsThe performances of each algorithm have been compared based on one metric—the geometric mean, also known as GMean (GM). This metric typically indicates the class-wise sensitivity by using the values of products. The findings of the study prove that the proposed MBSVM technique outperforms the other techniques.Research limitations/implicationsThis study provides an algorithm to predict ratings of banks where the dataset is small and imbalanced. One of the limitations of this research study is that subjective factors have not been included in our model; the sole focus is on the results generated by the models (driven by quantitative parameters). In future, studies may be conducted which may include subjective parameters (proxied by relevant and quantifiable variables).Practical implicationsVarious stakeholders such as investors, regulators and central banks can predict the credit ratings of banks by themselves, by inputting appropriate data to the model.Originality/valueIn the process of rating banks, the usage of an imbalanced dataset can lessen the performance of the soft-computing techniques. In order to overcome this, the authors have come up with a novel classification approach based on “MBSVMs”, which can be used as a yardstick for such imbalanced datasets. For this purpose, through primary research, 12 features have been identified that are considered essential by the credit rating agencies.
The role of social media advertising in hospitality, tourism and travel: a literature review and research agenda
Authors: Chu Shu-Chuan , Deng Tao , Cheng Hong 
Published: September 2020

Purpose
This study aims to provide an assessment of the existing literature on the role of social media advertising in hospitality, tourism and travel (HTT) as well as an agenda for future research.

Design/methodology/approach
Covering a 15-year time span (2004–2019), this study is focused on journal papers archived in two academic databases in social sciences: Business Source Complete and Communication and Mass Media Complete. Each of the 192 papers collected was coded for 8 major variables: journal, year of publication, research topic, country studied, type of social media investigated, method, theoretical underpinning and key findings.

Findings
Three major topic areas are identified in this study: use of social media from consumer’s perspective, use of social media from organization’s perspective and effects of social media.

Research limitations/implications
Although a few prior papers have provided a literature review of social media in tourism and hospitality, no review-based papers have ever examined social media as an advertising vehicle in the context of HTT. Most reviews to date have been limited to general social media studies, without much advancement of theory building in advertising research.

Originality/value
To the best of the authors’ knowledge, this paper represents the first theoretical review of academic research on social media advertising in HTT. The review concludes by suggesting a theoretical framework for studying social media advertising in HTT and offering an agenda for future research.
Artificial intelligence in the workplace – A double-edged sword
Authors: Wilkens Uta 
Published: September 2020

PurposeThe aim of this paper is to outline how artificial intelligence (AI) can augment learning process in the workplace and where there are limitations.Design/methodology/approachThe paper is a theoretical-based outline with reference to individual and organizational learning theory, which are related to machine learning methods as they are currently in use in the workplace. Based on these theoretical insights, the paper presents a qualitative evaluation of the augmentation potential of AI to assist individual and organizational learning in the workplace.FindingsThe core outcome is that there is an augmentation potential of AI to enhance individual learning and development in the workplace, which however should not be overestimated. AI has a complementarity to individual intelligence, which can lead to an advancement, especially in quality, accuracy and precision. Moreover, AI has a potential to support individual competence development and organizational learning processes. However, a further outcome is that AI in the workplace is a double-edged sword, as it easily shows reinforcement effects in individual and organizational learning, which have a backside of unintended effects.Research limitations/implicationsThe conceptual outline makes use of examples for illustrating phenomenon but needs further empirical analysis. The research focus on the meso level of the workplace does not fully refer to macro level outcomes.Practical implicationsThe practical implication is that it is a matter of socio-technical job design to integrate AI in the workplace in a valuable manner. There is a need to keep the human-in-the-loop and to complement AI-based learning approaches with non-AI counterparts to reach augmentation.Originality/valueThe paper faces workplace learning from an interdisciplinary perspective and bridges insights from learning theory with methods from the machine learning community. It directs the social science discourse on AI, which is often on macro level to the meso level of the workplace and related issues for job design and therefore provides a complementary perspective.