bluuebunny/crossref_metadata_2025_split huggingface dataset:
EMT-induced cell mechanical changes enhance mitotic rounding strength
Authors: Hosseini Kamran , Taubenberger Anna , Werner Carsten , Fischer-Friedrich Elisabeth 
Published: April 2019

AbstractTo undergo mitosis successfully, most animal cells need to acquire a round shape to provide space for the mitotic spindle. This mitotic rounding relies on mechanical deformation of surrounding tissue and is driven by forces emanating from actomyosin contractility. Cancer cells are able to maintain successful mitosis in mechanically challenging environments such as the increasingly crowded environment of a growing tumor, thus, suggesting an enhanced ability of mitotic rounding in cancer. Here, we show that epithelial mesenchymal transition (EMT), a hallmark of cancer progression and metastasis, gives rise to cell-mechanical changes in breast epithelial cells. These changes are opposite in interphase and mitosis and correspond to an enhanced mitotic rounding strength. Furthermore, we show that cell-mechanical changes correlate with a strong EMT-induced change in the activity of Rho GTPases RhoA and Rac1. Accordingly, we find that Rac1 inhibition rescues the EMT-induced cortex-mechanical phenotype. Our findings hint at a new role of EMT in successful mitotic rounding and division in mechanically confined environments such as a growing tumor.
Training and inferring neural network function with multi-agent reinforcement learning
Authors: Chalk Matthew , Tkacik Gasper , Marre Olivier 
Published: April 2019

AbstractA central goal in systems neuroscience is to understand the functions performed by neural circuits. Previous top-down models addressed this question by comparing the behaviour of an ideal model circuit, optimised to perform a given function, with neural recordings. However, this requires guessing in advance what function is being performed, which may not be possible for many neural systems. To address this, we propose a new framework for optimising a recurrent network using multi-agent reinforcement learning (RL). In this framework, a reward function quantifies how desirable each state of the network is for performing a given function. Each neuron is treated as an ‘agent’, which optimises its responses so as to drive the network towards rewarded states. Three applications follow from this. First, one can use multi-agent RL algorithms to optimise a recurrent neural network to perform diverse functions (e.g. efficient sensory coding or motor control). Second, one could use inverse RL to infer the function of a recorded neural network from data. Third, the theory predicts how neural networks should adapt their dynamics to maintain the same function when the external environment or network structure changes. This could lead to theoretical predictions about how neural network dynamics adapt to deal with cell death and/or varying sensory stimulus statistics.
Concordance of Race Documented in Electronic Health Records and Genetic Ancestry
Authors: Walunas Theresa L. , Pacheco Jennifer A. , Jackson Kathryn L. , Roberts Anna , Armstrong Loren L. , Behrens Jess , Hayes M. Geoffrey , Kho Abel N. 
Published: April 2019

ABSTRACTObjectiveGenetic screening is the gold standard for biogeographical ancestry (i.e. race), but this information is often unavailable to those developing research studies. We assessed agreement between census- and electronic health record (EHR)-derived demographic data with genetic ancestry to determine if these sources could support selection of diverse cohorts.Materials and MethodsWe identified a population of 4,837 genotyped patients and determined concordance between genetic measures of ancestry against race derived from decennial nationwide census, electronic medical records, and self-report.ResultsWe identified a 90% or greater concordance between the EHR-derived data and genetic ancestry. Census data had a high concordance (97%) with genetic and self-reported data for patients of European ancestry but low concordance for patients of African ancestry (64%).Discussion and ConclusionsThe high concordance between EHR-derived race and genetic ancestry suggests that EHR-derived information could be an effective proxy for race when recruiting for diverse research cohorts.
A divisive model of evidence accumulation explains uneven weighting of evidence over time
Authors: Keung Waitsang , Hagen Todd A. , Wilson Robert C. 
Published: April 2019

SummaryDivisive normalization has long been used to account for computations in various neural processes and behaviours. The model proposes that inputs into a neural system are divisively normalized by the total activity of the system. More recently, dynamical versions of divisive normalization have been shown to account for how neural activity evolves over time in value-based decision making. Despite its ubiquity, divisive normalization has not been studied in decisions that require evidence to be integrated over time. Such decisions are important when we do not have all the information available at once. A key feature of such decisions is how evidence is weighted over time, known as the integration ‘kernel’. Here we provide a formal expression for the integration kernel in divisive normalization, and show that divisive normalization can quantitatively account for the perceptual decision making behaviour of 133 human participants, performing as well as the state-of-the-art Drift Diffusion Model, the predominant model for perceptual evidence accumulation.
Nutritional ecology provides insights into competitive interactions between closely-related marten species
Authors: Gazzola Andrea , Balestrieri Alessandro 
Published: April 2019

AbstractFor generalist, closely-related predators as those belonging to the genusMartes, it is a hard task to differentiate the effects on feeding habits of variation in food availability from those of resource competition. To overcome this obstacle, we reviewed dietary studies that assessed the relative bulk of each food item, as either percent biomass or percent mean volume, in the diet of both the pine-(M. martes) and stone-(M. foina) marten, and calculated the nutrient profiles (intakes of protein, lipids and carbohydrates, expressed as percentages of total metabolizable energy) of each diet. Both martens’ diets tightly clustered (average values: 47% protein-, 39% lipid- and 14% carbohydrate energy), but, most interestingly, in allopatry the nutritional niches of the two species did not differ, while the stone marten ate more carbohydrates and less protein when sympatric with the pine marten. Our data suggest that stone marten frugivory is the result of interspecific competition.
Elevated LRRK2 and α-synuclein levels in CSF of infectious meningitis patients
Authors: Herbst Susanne , Marais Suzaan , Gutierrez Maximiliano G. , Waddell Simon J , Wilkinson Robert J. , Lai Rachel PJ 
Published: April 2019

AbstractNeurodegenerative diseases such as Parkinson’s (PD) have a complex aetiology consisting of an interplay of genetic and environmental factors. Inflammation and infection are proposed external factors that trigger disease progression. Tuberculous and cryptococcal meningitis frequently lead to long-term neurological sequelae but their association with the development of PD are unexplored. In this study, we protein profiled the CSF from 76 patients with or without infectious meningitis and found that proteins commonly associated with PD (LRRK2, tau and alpha-synuclein) were significantly elevated, establishing a link between neuroinflammation and infection. Importantly, these findings suggest that LRRK2, tau and alpha-synuclein could represent biomarkers of neuroinflammation.
A sparse EEG-informed fMRI model for hybrid EEG-fMRI neurofeedback prediction
Authors: Cury Claire , Maurel Pierre , Gribonval Rémi , Barillot Christian 
Published: April 2019

ABSTRACTMeasures of brain activity through functional magnetic resonance imaging (fMRI) or Electroencephalography (EEG), two complementary modalities, are ground solutions in the context of neuro-feedback (NF) mechanisms for brain rehabilitation protocols. While NF-EEG (real-time neurofeedback scores computed from EEG signals) have been explored for a very long time, NF-fMRI (real-time neurofeedback scores computed from fMRI signals) appeared more recently and provides more robust results and more specific brain training. Using simultaneously fMRI and EEG for bi-modal neurofeedback sessions (NF-EEG-fMRI, real-time neurofeedback scores computed from fMRI and EEG) is very promising to devise brain rehabilitation protocols. However, fMRI is cumbersome and more exhausting for patients. The original contribution of this paper concerns the prediction of bi-modal NF scores from EEG recordings only, using a training phase where EEG signals as well as the NF-EEG and NF-fMRI scores are available. We propose a sparse regression model able to exploit EEG only to predict NF-fMRI or NF-EEG-fMRI in motor imagery tasks. We compared different NF-predictors steaming from the proposed model. We showed that predicting NF-fMRI scores from EEG signals adds information to NF-EEG scores and significantly improve the correlation with bi-modal NF sessions, compared to classical NF-EEG scores.
Serum proteomic approach for differentiation of frail and non-frail elderly
Authors: Agnihotri Vertica , Gupta Abhishek , Pradhan Rashmita , Venugopalan G , Bajpai Sailesh , Dey A. B. , Dey Sharmistha 
Published: April 2019

AbstractFrail elderly is very common in Indian society and extremely difficult to manage in the clinical practice. Blood proteomic study may able to improve the specific diagnostic profiles and therapeutic templates for improving quality of life in elderly. The purpose of present study is to differentiate between frail and non-frail elderly on the basis of serum markers. The proteomic profile of 10 frail and 10 non-frail elderly diagnosed according to deficit accumulation model of Rockwood was identified by 2D-electrophoresis and analyzed using ImageMaster 2DPlatinum7.0 software. The proteins were identified by MALDI-TOF/TOF and performed gene ontology study by PANTHER 7.0 software. Overall 105 spots were identified in the study groups. In frail 22spots and in non-frail 12spots were found to be differentially expressed. Mass spectroscopy analysis of 13 spots showed up-regulated Haptoglobin, Serum amyloidA1, TRAK1, sp110, NLRC3, MMP12, Mortalin, NDK3 and downregulated PSRC1, NKG2A proteins in frail elderly. The differential expression of proteins in frailty are mostly associated with pro-inflammation and is well-known that frailty syndrome increases all inflammatory parameters. It can be summarized from the present proteomic study that these proteins can be used as potential biomarkers for early detection of frailty in the elderly.
Bet-hedging across generations can affect the evolution of variance-sensitive strategies within generations
Authors: Haaland Thomas R. , Wright Jonathan , Ratikainen Irja I. 
Published: April 2019

AbstractIn order to understand how organisms cope with ongoing changes in environmental variability it is important to consider all types of adaptations to environmental uncertainty on different time-scales. Conservative bet-hedging represents a long-term genotype-level strategy that maximizes lineage geometric mean fitness in stochastic environments by decreasing individual fitness variance, despite also lowering arithmetic mean fitness. Meanwhile, variance-prone (aka risk-prone) strategies produce greater variance in short-term payoffs because this increases expected arithmetic mean fitness if the relationship between payoffs and fitness is accelerating. Using two evolutionary simulation models, we investigate whether selection for such variance-prone strategies are counteracted by selection for bet-hedging that works to adaptively reduce fitness variance. We predict that variance-prone strategies will be favored in scenarios with more decision events per lifetime and when fitness accumulates additively rather than multiplicatively. In our model variance-proneness evolved in fine-grained environments (with lower correlations among individuals in energetic state and/or in payoffs when choosing the variable decision), and with larger numbers of independent decision events over which resources accumulate prior to selection. In contrast, geometric fitness accumulation caused by coarser environmental grain and fewer decision events prior to selection favors conservative bet-hedging via greater variance-aversion. We discuss examples of variance-sensitive strategies in optimal foraging, migration, life histories and cooperative breeding in light of these results concerning bet-hedging. By linking disparate fields of research studying adaptations to variable environments we should be more able to understand the effects in nature of human-induced rapid environmental change.Data depositionR code is available upon request.
The cerebellum is involved in processing of predictions and prediction errors in a fear conditioning paradigm
Authors: Ernst TM , Brol A , Gratz M , Ritter C , Bingel U , Schlamann M , Maderwald S , Quick HH , Merz CJ , Timmann D 
Published: April 2019

AbstractPrediction errors are thought to drive associative fear learning. Surprisingly little is known about the possible contribution of the cerebellum. To address this question, healthy participants underwent a differential fear conditioning paradigm during 7T magnetic resonance imaging. An event-related design allowed us to separate cerebellar fMRI signals related to the visual conditioned stimulus (CS) from signals related to the subsequent unconditioned stimulus (US; an aversive electric shock). We found significant activation of cerebellar lobules Crus I and VI bilaterally related to the CS+ compared to the CS-. Most importantly, significant activation of lobules Crus I and VI was also present during the unexpected omission of the US in unreinforced CS+ acquisition trials. This activation disappeared during extinction when US omission became expected. These findings provide evidence that the cerebellum has to be added to the neural network processing predictions and prediction errors in the emotional domain.
Pseudogenization, genome streamlining and specific gene repertoire landmark the genomes ofCarnobacterium maltaromaticumisolated from diseased sharks
Authors: Steele Laura Martinez , Lowe Christopher G , Okihiro Mark S , Dillon Jesse G. , Berlemont Renaud 
Published: April 2019

AbstractCarnobacterium maltaromaticumis a well-known pathogen of bony fish. More recently,C. maltaromaticumhave been isolated from the brain and inner ear of disorientated and stranded common thresher (Alopias vulpinus) and salmon shark (Lamna ditropis). While thresher shark strandings are recent, salmon sharks have been stranding for decades, suggesting a long-term association betweenC. maltaromaticumand sharks. Interestingly, some strains ofC. maltaromaticumare used by the food industry for their probiotic and antimicrobial activity. Here, we sequenced the genome of 9C. maltaromaticumstrains (SK-isolates) from diseased common thresher and salmon sharks and compared them to otherC. maltaromaticumstrains in order to identify the genomic signatures that differentiate the disease-associated from the innocuousC. maltaromaticumisolates. SK strains formed a monophyletic clade, with a conserved gene repertoire, and shared a high degree of pseudogenization even though isolates were from different shark species, locations, and across years. In addition, these strains displayed few virulence associated genes and unique genomic regions, some resulting from horizontal gene transfer. The association of diseased sharks and SK strains suggests their role as potential pathogens. Although the high degree of pseudogenization suggests a transition to a host-adapted lifestyle, a set of conserved functional genes highlights the need of essential functions required for a host-independent life style. Globally, this work identifies specific genomic signatures ofC. maltaromaticumstrains isolated from infected sharks, provides the framework to elucidate the role of SK strains in the development of the disease in sharks, and further investigate the dissemination of SK strains in populations of wild fish.
A modeling algorithm for exploring the architecture and construction of bird nests
Authors: Jessel Hadass R. , Aharoni Lior , Efroni Sol , Bachelet Ido 
Published: April 2019

AbstractNatural biological structures are often complex and cannot be mapped directly to genes, being therefore impossible to explore by traditional biological tools. In contrast, digitizing these structures enables to explore their properties and behavior under specific conditions, by means of computational manipulations, simulations, and analyses. We describe a generic algorithm for the digitization and exploration of the complex structures exhibited by common, interwoven bird nests. This algorithm takes as input computerized tomographic scans of the studied Dead-Sea Sparrow (Passer moabiticus) nest, identifies and isolates each branch entity within the three-dimensional data and finally extracts the characteristics of each branch. The result is a reliable three-dimensional numerical model of the nest that contains a complete geometric dataset per each of its components, e.g. dimensions and contact points with neighboring components, as well as global properties, e.g. density distribution and network structure. Based on these, we were able to simulate various models of the nest construction process. Altogether, the described algorithm and possible derivatives thereof could be a valuable tool in studying the structure-function relationships of similarly complex biological objects.
Can students be taught to articulate employability skills?
Authors: Tomasson Goodwin Jill , Goh Joslin , Verkoeyen Stephanie , Lithgow Katherine 
Published: April 2019

Purpose
The purpose of this paper is to report on research findings from a teaching and learning intervention that explored whether undergraduate university students can be taught to articulate their employability skills effectively to prospective employers and to retain this ability post-course.

Design/methodology/approach
The study included 3,400 students in 44 courses at a large Canadian university. Stage 1 involved a course-level teaching and learning intervention with the experimental student group, which received employability skills articulation instruction. Stage 2 involved an online survey administered six months post-course to the experimental group and the control group. Both groups responded to two randomly generated questions using the Situation/Task, Actions, Result (STAR) format, a format that employers commonly rely on to assess job candidates’ employability skills. The researchers compared the survey responses from the experimental and control groups.

Findings
Survey results demonstrate that previous exposure to the STAR format was the only significant factor affecting students’ skills articulation ability. Year of study and program (co-operative or non-co-operative) did not influence articulation.

Practical implications
The findings suggest that universities should integrate institution-wide, course-level employability skills articulation assignments for students in all years of study and programs (co-op and non-co-op).

Originality/value
This research is novel because its study design combines practical, instructional design with empirical research of significant scope (institution-wide) and participant size (3,400 students), contributing quantitative evidence to the employability skills articulation discussion. By surveying students six months post-course, the study captures whether articulation instruction can be recalled, an ability of particular relevance for career preparedness.
Student perceptions of virtual reality use in higher education
Authors: Baxter Gavin , Hainey Thomas 
Published: April 2019

Purpose
This paper provides an analysis and insight into undergraduate student views concerning the use of virtual reality technology towards whether it has the potential to support and provide novel pedagogical avenues towards teaching and learning in higher education. The purpose of this paper is to ascertain student views about the application of VR technology within their degree programmes from a pedagogical perspective in addition to identifying potential challenges to VR adoption.

Design/methodology/approach
The research design adopted a mixed methods approach through the use of a questionnaire that was disseminated to undergraduate students studying in the discipline area of the creative industries. Through a series of open and closed questions, student views on VR adoption in higher education were analysed both quantitatively and qualitatively. The results were analysed statistically through a series of Mann–Whitney and Kruskal–Wallis tests. The qualitative statements were contextualised in the overall perspective of the research with the more relevant viewpoints identified to coincide with aspects of VR discovered in the literature.

Findings
The predominant findings of the research indicated that the majority of the students considered the use of VR to have useful pedagogical implications though not all findings were positive. The findings provided a sound overview of the benefits and potential drawbacks of VR use in general with a more specific focus in an educational context.

Research limitations/implications
Limitations of the research include the lack of overall generalisations that can be formed from the study due to the sample size and the fact that the results were based from one specific academic institution.

Practical implications
The findings of the research will provide educators with an insight into various perceptions of VR adoption within higher education. This will aid towards allowing them to reflect on whether VR is an appropriate tool to integrate within their curriculum and pedagogical approaches towards course delivery.

Originality/value
Though several studies have explored the use of VR in multiple contexts and subject areas, there still needs to be more research towards its potential drawbacks in a teaching and learning scenario and how to resolve these issues.