bluuebunny/crossref_metadata_2025 huggingface dataset:
Differential Transcript Usage Analysis Incorporating Quantification Uncertainty Via Compositional Measurement Error Regression Modeling
Authors: Van Buren Scott , Rashid Naim
Published: May 2020

Differential transcript usage (DTU) occurs when the relative transcript abundance of a gene changes between different conditions. Existing approaches to analyze DTU often rely on computational procedures that can have speed and scalability issues as the number of samples increases. In this paper, we propose a new method, termedCompDTU, that utilizes compositional regression to model transcript-level relative abundance proportions that are of interest in DTU analyses. This procedure does not suffer from speed and scalability issues due to the relative computational simplicity, making it ideally suited for DTU analysis with large sample sizes. The method also allows for the testing of and controlling for multiple categorical or continuous covariates. Additionally, many existing approaches for DTU ignore quantification uncertainty present in RNA-Seq data, where prior work has shown that accounting for such uncertainty may improve testing performance. We extend ourCompDTUmethod to incorporate quantification uncertainty using bootstrap replicates of abundance estimates fromSalmonand term this methodCompDTUme. Through several power analyses, we show thatCompDTUimproves sensitivity and reduces false positive results relative to existing methods. Additionally,CompDTUmeresults in further improvements in performance overCompDTUwith sufficient sample size for genes with high levels of quantification uncertainty while maintaining favorable speed and scalability.
In silico detection of SARS-CoV-2 specific B-cell epitopes and validation in ELISA for serological diagnosis of COVID-19
Authors: Phan Isabelle Q. , Subramanian Sandhya , Kim David , Carter Lauren , King Neil , Anishchenko Ivan , Barrett Lynn K. , Craig Justin , Tillery Logan , Shek Roger , Harrington Whitney E. , Koelle David M. , Wald Anna , Boonyaratanakornkit Jim , Isoherranen Nina , Greninger Alexander L. , Jerome Keith R. , Chu Helen , Staker Bart , Stewart Lance , Myler Peter J. , Van Voorhis Wesley C.
Published: May 2020

Rapid generation of diagnostics is paramount to understand epidemiology and to control the spread of emerging infectious diseases such as COVID-19. Computational methods to predict serodiagnostic epitopes that are specific for the pathogen could help accelerate the development of new diagnostics. A systematic survey of 27 SARS-CoV-2 proteins was conducted to assess whether existing B-cell epitope prediction methods, combined with comprehensive mining of sequence databases and structural data, could predict whether a particular protein would be suitable for serodiagnosis. Nine of the predictions were validated with recombinant SARS-CoV-2 proteins in the ELISA format using plasma and sera from patients with SARS-CoV-2 infection, and a further 11 predictions were compared to the recent literature. Results appeared to be in agreement with 12 of the predictions, in disagreement with 3, while a further 5 were deemed inconclusive. We showed that two of our top five candidates, the N-terminal fragment of the nucleoprotein and the receptor-binding domain of the spike protein, have the highest sensitivity and specificity and signal-to-noise ratio for detecting COVID-19 sera/plasma by ELISA. Mixing the two antigens together for coating ELISA plates led to a sensitivity of 94% (N=80 samples from persons with RT-PCR confirmed SARS-CoV2 infection), and a specificity of 97.2% (N=106 control samples).
Bayesian analysis of tests with unknown specificity and sensitivity
Authors: Gelman Andrew , Carpenter Bob
Published: May 2020

When testing for a rare disease, prevalence estimates can be highly sensitive to uncertainty in the specificity and sensitivity of the test. Bayesian inference is a natural way to propagate these uncertainties, with hierarchical modeling capturing variation in these parameters across experiments. Another concern is the people in the sample not being representative of the general population. Statistical adjustment cannot with- out strong assumptions correct for selection bias in an opt-in sample, but multilevel regression and poststratification can at least adjust for known differences between the sample and the population. We demonstrate hierarchical regression and poststratification models with code in Stan and discuss their application to a controversial recent study of SARS-CoV-2 antibodies in a sample of people from the Stanford University area. Wide posterior intervals make it impossible to evaluate the quantitative claims of that study regarding the number of unreported infections. For future studies, the methods described here should facilitate more accurate estimates of disease prevalence from imperfect tests performed on non-representative samples.
COVID-19 Outcomes in 4712 consecutively confirmed SARS-CoV2 cases in the city of Madrid
Authors: Heili-Frades Sarah , Minguez Pablo , Fernández Ignacio Mahillo , Prieto-Rumeau Tomás , González Antonio Herrero , de la Fuente Lorena , Nieto María Jesús Rodríguez , Romero Germán Peces-Barba , Peces-Barba Mario , del Pilar Carballosa de Miguel María , Ormaechea Itziar Fernández , prieto Alba Naya , de Blas Farah Ezzine , Hiscock Luis Jiménez , Calvo Cesar Perez , Santos Arnoldo , Alameda Luis Enrique Muñoz , Bueno Fredeswinda Romero , Hernández-Mora Miguel Górgolas , Úbeda Alfonso Cabello , Álvarez Beatriz Álvarez , Petkova Elizabet , Carrasco Nerea , Ríos Dolores Martín , Mangado Nicolás González , Pernaute Olga Sánchez ,   and the COVID FJD-TEAM
Published: May 2020

There is limited information describing features and outcomes of patients requiring hospitalization for COVID19 disease and still no treatments have clearly demonstrated efficacy. Demographics and clinical variables on admission, as well as laboratory markers and therapeutic interventions were extracted from electronic Clinical Records (eCR) in 4712 SARS-CoV2 infected patients attending 4 public Hospitals in Madrid. Patients were stratified according to age and stage of severity. Using multivariate logistic regression analysis, cut-off points that best discriminated mortality were obtained for each of the studied variables. Principal components analysis and a neural network (NN) algorithm were applied.

A high mortality incidence associated to age >70, comorbidities (hypertension, neurological disorders and diabetes), altered vitals such as fever, heart rhythm disturbances or elevated systolic blood pressure, and alterations in several laboratory tests. Remarkably, analysis of therapeutic options either taken individually or in combination drew a universal relationship between the use of Cyclosporine A and better outcomes as also a benefit of tocilizumab and/or corticosteroids in critically ill patients.

We present a large Spanish population-based study addressing factors influencing survival in current SARS CoV2 pandemic, with particular emphasis on the effectivity of treatments. In addition, we have generated an NN capable of identifying severity predictors of SARS CoV2. A rapid extraction and management of data protocol from eCR and artificial intelligence in-house implementations allowed us to perform almost real time monitoring of the outbreak evolution.
Bi-allelic variants inTSPOAP1, encoding the active zone protein RIMBP1, cause autosomal recessive dystonia
Authors: Mencacci Niccolò E. , Brockmann Marisa M. , Dai Jinye , Pajusalu Sander , Atasu Burcu , Gonzalez-Latapi Paulina , Patzke Christopher , Schwake Michael , Tucci Arianna , Pittman Alan , Simon-Sanchez Javier , Carvill Gemma L. , Balint Bettina , Wiethoff Sarah , Warner Thomas T. , Papandreou Apostolos , Soo Audrey , Rein Reet , Kadastik-Eerme Liis , Puusepp Sanna , Reinson Karit , Tomberg Tiiu , Campos Joaquin , Pino Gabriela , Hanagasi Hasmet , Gasser Thomas , Bhatia Kailash P. , Kurian Manju A. , Lohmann Ebba , Õunap Katrin , Rosenmund Christian , Südhof Thomas C. , Wood Nicholas W. , Krainc Dimitri , Acuna Claudio
Published: May 2020

Dystonia is a debilitating hyperkinetic movement disorder, frequently transmitted as a monogenic trait. Here, we describe homozygous frameshift, nonsense and missense variants inTSPOAP1, encoding the active zone RIM-binding protein 1 (RIMBP1), as a novel genetic cause of autosomal recessive dystonia in seven subjects from three unrelated families. Subjects carrying loss-of-function variants presented with juvenile- onset progressive generalized dystonia, associated with intellectual disability and cerebellar atrophy. Conversely, subjects carrying a pathogenic missense variant (p.Gly1808Ser) presented with isolated adult-onset focal dystonia. In mice, complete loss of RIMBP1, known to reduce neurotransmission, led to motor abnormalities reminiscent of dystonia, decreased Purkinje cell dendritic arborization, and reduced numbers of cerebellar synapses. In vitro analysis of the p.Gly1808Ser variant showed larger spike-evoked calcium transients and enhanced neurotransmission, suggesting that RIMBP1-linked dystonia can be caused by either reduced or enhanced rates of spike-evoked release in relevant neural networks. Our findings establish a direct link between presynaptic RIMBP1 dysfunction and dystonia and highlight the critical role played by well-balanced neurotransmission in motor control and disease pathogenesis.
Nanopore sequencing enables comprehensive transposable element epigenomic profiling
Authors: Ewing Adam D. , Smits Nathan , Sanchez-Luque Francisco J. , Faivre Jamila , Brennan Paul M. , Cheetham Seth W. , Faulkner Geoffrey J.
Published: May 2020

We apply long-read nanopore sequencing and a new tool, TLDR (Transposons from Long Dirty Reads), to directly infer CpG methylation of new and extant human transposable element (TE) insertions in hippocampus, heart, and liver, as well as paired tumour and non-tumour liver. Whole genome TLDR analysis greatly facilitates studies of TE biology as complete insertion sequences and their epigenetic modifications are readily obtainable.
Gut microbial ecology of Xenopus tadpoles across life stages
Authors: Scalvenzi Thibault , Clavereau Isabelle , Bourge Mickaël , Pollet Nicolas
Published: May 2020

Background

The microorganism world living in amphibians is still largely under-represented and under-studied in the literature. Among anuran amphibians, African clawed frogs of theXenopusgenus stand as well-characterized models with an in-depth knowledge of their developmental biological processes including their metamorphosis. In this study, we analyzed the succession of microbial communities and their activities across diverse body habitats ofXenopus tropicalisusing different approaches including flow cytometry and 16s rDNA gene metabarcoding. We also evaluated the metabolic capacity of the premetamorphic tadpole’s gut microbiome using metagenomic and metatranscriptomic sequencing.

Results

We analyzed the bacterial components of theXenopusgut microbiota, the adult gut biogeography, the succession of communities during ontogeny, the impact of the alimentation in shaping the tadpole’s gut bacterial communities and the transmission of skin and fecal bacteria to the eggs. We also identified the most active gut bacteria and their metabolic contribution to tadpole physiology including carbohydrate breakdown, nitrogen recycling, essential amino-acids and vitamin biosynthesis.

Conclusions

We present a comprehensive new microbiome dataset of a laboratory amphibian model. Our data provide evidences that studies on theXenopustadpole model can shed light on the interactions between a vertebrate host and its microbiome. We interpret our findings in light of bile acids being key molecular components regulating the gut microbiome composition during amphibian development and metamorphosis. Further studies into the metabolic interactions between amphibian tadpoles and their microbiota during early development and metamorphosis should provide useful information on the evolution of host-microbiota interactions in vertebrates.

This article has been peer-reviewed and recommended byPeer Community in Genomicshttps://doi.org/10.24072/pci.genomics.100005
A non-parametric analysis of the effect of the configuration of competitive pillars on competitive efficiency
Authors: Horváth Krisztina , Lafuente Esteban
Published: May 2020

Purpose

This study aims to evaluate how the configuration of competitive pillars impacts businesses' competitive efficiency by using a non-parametric model, namely, data envelopment analysis (DEA), with a single constant input.

Design/methodology/approach

The proposed DEA model evaluates technical inefficiency, which results from differences in the availability and allocation of resources, and configuration inefficiency, which we link to differences in the way businesses amalgamate their competitive pillars. The sample includes 115 Spanish businesses operating in manufacturing, construction, retail and knowledge-intensive business services (KIBS) sectors.

Findings

The results reveal that, on an average, firms can improve their overall competitive efficiency by 53.53%. The findings suggest that the configuration of competitive pillars has important implications for efficiency analyses: human capital and strategy are the most relevant aspects shaping competitive efficiency in manufacturing and construction firms; whereas innovation emerges as the most relevant competitive aspect driving competitive efficiency in KIBS firms.

Originality/value

The novelty of this study lies in the analysis of competitive efficiency in a model where efficiency can be explained by overall (industry-specific) competitive efficiency within the industry and by strategic choices on how resources and capabilities are combined within the business.
Entrepreneurial learning as practice: a video-ethnographic analysis
Authors: Thompson Neil Aaron , Illes Edina
Published: May 2020

Purpose

Despite the gains that have been made by adopting contemporary theories of practice in entrepreneurship studies, the field still lacks a comprehensive practice theory of entrepreneurial learning. In this article, we develop a practice theory of entrepreneurial learning by elaborating on the relations between practicing, knowing and learning.

Design/methodology/approach

Using a video ethnography of a two-day “Startup Weekend for Refugees” event in Amsterdam, our aim is to further theorise the relational, material and embodied nature of entrepreneurial learning through analysing video fragments of naturally occurring practices.

Findings

Our findings demonstrate that entrepreneurial learning transpires through, and is emergent from, practices and their relations. On the one hand, practitioners learn to competently participate in various practices by sensing, observing and experimenting with the meaning of others' gestures and utterances. On the other, the learning of new opportunities for value creation emerges as practitioners connect various practices to one another through translation.

Originality/value

This article contributes by illustrating and explaining real-time instances of learning to develop a practice theory of entrepreneurial learning. This contributes to the literature by detailing the relations between learning, knowing and practising entrepreneurship, which leads to a novel alternative to existing individual- and organisational-level learning theories.
The best equilibrium in organizational flexibility-stability continuums
Authors: Laser Jan
Published: May 2020

Purpose

This work aims to analyse the flexibility-stability continuum and explore the question of where the best equilibrium lies on this continuum and to what extent it can be realized.

Design/methodology/approach

After analysing the concepts of flexibility and stability, along with their trade-off relationship, from a theoretical standpoint, the optimum in the flexibility-stability continuum is determined by means of a triangulation of theories. The subsequent operation to determine best possible practice is also accomplished via a theoretical analysis.

Findings

Organizational flexibility and stability are two poles of a continuum that are interdependent. The optimum in a flexibility-stability continuum lies, according to Gossen's first law, where marginal utility is zero. Determination of the optimum requires a great deal of information, however, which is difficult to collate and process because of its complexity. As an alternative to the “optimum”, “best possible practice” is introduced. This provides an alternative to the less satisfactory method of “best practice according to benchmarking.”

Originality/value

The value of this work lies in finding an optimum in the flexibility-stability continuum. As the (theoretical) optimum is difficult to determine and realize due to inherent complexities, “best possible practice” is presented as an alternative. This takes into account the idea of optimization meaning no improvement is possible if the goal is achieved. “Best possible practice” defines an implementable, best possible state that can be used for organizational goal formulation. To achieve the best possible equilibrium in the flexibility-stability continuum, the respective advantages of stability and flexibility should be ideally exploited to lead to competitive advantage.
Explaining stock market returns in Sub-Saharan Africa using an alternate uncovered interest rate parity framework
Authors: Bondzie Afful Kofi , Opoku William
Published: May 2020

Purpose

Sub-Saharan African (SSA) stock exchanges are imperfect and inefficient. Therefore, orthodox finance theories are unable to completely explain their market returns. Such models mainly identify anomalies when applied to the sub-region. Consequently, this paper develops an original theoretical model to better explain market returns on the sub-continent.

Design/methodology/approach

This paper develops an alternate analytical framework that combines adaptive expectations, Keynesian LM model and modified uncovered interest parity (UIP) formulations to address empirical anomalies identified by previous literature when analyzing SSA's inefficient stock markets. Using panel data, the study first computes the fixed as well as random effects regressions and, later, a Generalized Method of Moments (GMM) dynamic panel regression for further empirical analysis.

Findings

Both the fixed and random effects regression results indicate that the relative output-money supply disparity and foreign inflation-money supply growth rate spread have positive effects on market returns in SSA. On the other hand, foreign interest rates have an inverse effect. Although the GMM dynamic panel regression has similar results, it additionally finds that market returns in SSA are autoregressive. This suggests that past returns are persistent.

Research limitations/implications

A key implication is that multipliers and transmission mechanisms in SSA may take longer to adjust, thereby limiting short-run market returns. Also, policymakers must encourage a critical mass of firms to list in order to enhance efficiency. Additionally, policy variables significantly influence returns. One limitation is the high market segmentation in SSA. This heightens heterogeneity, emphasizing fixed effects.

Practical implications

Also, the findings of this study may not apply to all emerging economies as SSA economies are highly heterogeneous.

Social implications

The segmented nature of SSA stock markets may have implications for income inequality and the distribution of resources within the economy. Also, it indicates that there are limits to how firms use capital markets on the sub-continent.

Originality/value

This paper abstracts from the strict ideal market conditions prescribed by modern finance theories and develops an original modified UIP model. It finds that SSA stock markets may be more sensitive to policy variables, instead of determinants postulated by orthodox finance concepts. The study offers opportunities for further critical examination of returns in imperfect frontier markets.
Reliability analysis of a steam boiler system by expert judgment method and best-fit failure model method: a new approach
Authors: Patil Suyog Subhash , Bewoor Anand K.
Published: May 2020

Purpose

India's textile industries play a vital role in the Indian economy. These industries consume the highest thermal energy (steam power). The demand of the steam in process industries is increasing rapidly, and this demand can be met by increasing the capacity utilization of steam boilers. The purpose of this paper is to present a new approach for reliability analysis by expert judgment method.

Design/methodology/approach

A lack of adequate life data is one of the biggest challenge in the reliability analysis of mechanical systems. This research provides an expert judgment approach for assessing the boiler's reliability characteristics. For this purpose, opinions of experts on time to failure and time to repair data were elicited in the form of statistical distributions. In this work, reliability analysis of the boiler system is carried out by expert judgment method and by using best-fit failure model. The system reliability along with preventive maintenance intervals of all components is also evaluated.

Findings

It is observed that the reliability analysis results obtained by expert judgment method and best-fit failure model method indicate that there are no significant differences. Therefore, in case when insufficient data are available, the expert judgment method can be effectively used. The analysis shows that the feedwater tank, feedwater pump, supply water temperature sensor, strainer, return water temperature sensor, condensate filter, mechanical dust collector, coal crusher and fusible plug are identified as critical components from a reliability perspective, and preventive maintenance strategy is suggested for these components.

Originality/value

In this research paper, a system reliability model by the expert judgment method is developed, and it can be effectively used where insufficient failure data are available. This paper is useful for the comparative evaluation of reliability characteristics of a boiler system by expert judgment method and best-fit failure model method.
Field data for satellite validation and forest structure modeling in a pure and sparse forest of Picea glehnii in northern Hokkaido
Authors: Akitsu Tomoko K. , Nakaji Tatsuro , Yoshida Toshiya , Sakai Rei , Mamiya Wataru , Terigele  , Takagi Kentaro , Honda Yoshiaki , Kajiwara Koji , Nasahara Kenlo N.
Published: May 2020

To validate and to improve ecological products obtained from satellites, such as a leaf area index (LAI), above‐ground biomass (AGB), and a fraction of photosynthetically active radiation (fAPAR), in‐situ accurate data are indispensable. They must be not a single point‐data but an areal data representing the satellite footprint. Their accuracy needs to be much higher than the required accuracy for the satellite products. The quantitative assessment of their error is necessary for evaluating the satellite products' error from the discrepancy between the satellite products and the in‐situ data. However, such data had not been available. In particular, there had been few data of LAI in a sparse evergreen needle‐leaved forest, because of difficulty of accuracy control of in‐situ observation in such a forest. To overcome the difficulty and to obtain the representative LAI, we made an allometric equation to estimate the leaf mass of Picea glehnii in northern Hokkaido. We report the allometric equations of leaf mass and AGB of P. glehnii, its leaf mass per area (LMA), its leaf life span, its leaf distribution, its crown shapes, its wood specific gravity, and tree locations. We also report LAI, AGB, and fAPAR within the 500 m × 500 m area, which is the footprint scale of the Global Change Observation Mission‐Climate satellite, in a pure and sparse forest of P. glehnii in northern Hokkaido. These precise data are useful for validation of other satellite data, especially with higher spatial resolution, and forest structure modeling.

The complete data set for this abstract published in the Data Paper section of the journal is available in electronic format in MetaCat in JaLTER at http://db.cger.nies.go.jp/JaLTER/metacat/metacat/ERDP-2020-06.1/jalter-en. [Correction added on 7 September 2020, after first online publication: JaLTER URL has been updated.]
‘Willy nilly’ doctors, bad patients, and resistant bodies in general public explanations of antimicrobial resistance
Authors: Davis Mark D. M. , Lohm Davina B. , Whittaker Andrea , Flowers Paul
Published: May 2020

Increased public engagement is a feature of policy and communications focussed on the reduction of antimicrobial resistance. Explaining antimicrobial resistance for general publics has proven difficult and they continue to endorse apparently mistaken knowledge, including the conflation of antimicrobial resistance with the notion of the resistant body. We interviewed members of the general public in Melbourne, Australia, to explore explanatory models for antimicrobial resistance and shed light on the persistence of the resistant body assumption and related concepts. In the face of AMR’s complexity and the portended antibiotic apocalypse, publics rely on a heavily inscribed understanding of the body defending itself against microbes. Publics also read antibiotic misuse and overuse messages as the responsibility of other patients and medical practitioners, and not themselves. Significantly, the scientific world view that has created expert knowledge about AMR hails publics in ways that discredits them and limits their capacity to take action. Increased engagement with publics will be required to ensure that collaborative and sustainable AMR approaches are fashioned for the future.
Analysis on physicochemical and sensory qualities of soymilk prepared by various cultivars: Application of fuzzy logic technique
Authors: Jin Xuehua , Chen Chen , Guo Shuntang , Zhang Hui
Published: May 2020

Soymilk has a complicated system, and its sensory and physicochemical characteristics are influenced by the components of the soybean seeds. Thirty‐five soybean cultivars were selected, and correlation analysis and clustering analysis were applied to determine the significant correlations between soybean seed traits and soymilk physiochemical properties. Four sensory quality attributes of soymilk, including taste, odor, appearance, and mouthfeel, were quantified in numerical values and scored based on a weighting criterion which was constructed via the fuzzy logic technique. Soymilk prepared from the soybean seeds with the lower crude protein and the higher crude fat content displayed better sensory qualities. A multivariate linear regression analysis was used to establish a predictive model for overall sensory scores of soymilk, which could be the reference for soybean cultivars selection in soymilk processing. To comprehensively optimize the processing costs, nutritional values, and sensory qualities, a set of detailed attributes of soybean seeds were recommended based on this study: 100‐seed weight is higher than 20 g; ash content is less than 5.5 g/100 g; crude fat content is 20 to 24 g/100 g; and crude protein content is as high as possible, while the maximum limit is 40 g/100 g.

Practical Application

The established predictive model can be a reference for soybean cultivars selection in soymilk processing. Moreover, the soybean composition range that is revealed by this study also provides a recommendation for the soybean breeding.
Fast quantification of short‐chain fatty acids in rat plasma by gas chromatography
Authors: Wang Chung‐Yi , Chen Yu‐Wei , Tain You‐Lin , Chang Sam K.C. , Huang Li‐Tung , Hsieh Chang‐Wei , Hou Chih‐Yao
Published: May 2020

Short‐chain fatty acids (SCFAs) are the main metabolites of the intestinal flora and play an important role in the interaction between the intestinal flora and host metabolism. Therefore, reliable methods are needed to accurately measure SCFAs concentrations. SCFAs are commonly analyzed by gas chromatography–mass spectrometry (GC‐MS), which requires lengthy sample treatments and a long run time. This study aimed to develop a fast GC method with formic acid pretreatment for SCFAs quantification in the plasma of rat. Baseline chromatographic resolution was achieved for three SCFAs (acetic, propionic, and butyric) within an analysis time of 10.5 min. The method exhibited good recovery for a wide range of concentrations with a low limit of detection for each compound. The relative standard deviations (RSDs) of all targeted compounds showed good intra‐ and interday precision (<10%). We used our method to measure SCFAs levels in plasma samples from rats fed with a high fructose diet (HFD) to test the accuracy of the developed method. It was shown that SCFAs are indeed affected negatively by a HFD (60% fructose). This method was successfully employed to accurately determine SCFAs in the rat plasma with minimum sample preparation. Results showed potential damage of HFD, which produced lower SCFAs.

Practical Application

Increasingly, microbiota and gut health research are being conducted by many food scientists to elucidate the relationships among the factors of food components, particularly the nondigestible carbohydrates, food processing conditions, and potential health impact. This research provides a useful, rapid, and accurate method that can save time in the analysis of short‐chain fatty acids, which are commonly analyzed in gut health research.
Association between algal productivity and phycosphere composition in an outdoor Chlorella sorokiniana reactor based on multiple longitudinal analyses
Authors: Steichen Seth A. , Gao Song , Waller Peter , Brown Judith K.
Published: May 2020

Microalgae as a biofuel source are of great interest. Bacterial phycosphere inhabitants of algal cultures are hypothesized to contribute to productivity. In this study, the bacterial composition of the Chlorella sorokiniana phycosphere was determined over several production cycles in different growing seasons by 16S rRNA gene sequencing and identification. The diversity of the phycosphere increased with time during each individual reactor run, based on Faith’s phylogenetic diversity metric versus days post‐inoculation (R = 0.66, P < 0.001). During summer months, Vampirovibrio chlorellavorus, an obligate predatory bacterium, was prevalent. Bacterial sequences assigned to the Rhizobiales, Betaproteobacteriales and Chitinophagales were positively associated with algal biomass productivity. Applications of the general biocide, benzalkonium chloride, to a subset of experiments intended to abate V. chlorellavorus appeared to temporarily suppress phycosphere bacterial growth, however, there was no relationship between those bacterial taxa suppressed by benzalkonium chloride and their association with algal productivity, based on multinomial model correlations. Algal health was approximated using a model‐based metric, or the ‘Health Index’ that indicated a robust, positive relationship between C. sorokiniana fitness and presence of members belonging to the Burholderiaceae and Allorhizobium–Neorhizobium–Pararhizobium–Rhizobium clade. Bacterial community composition was linked to the efficiency of microalgal biomass production and algal health.
Multilevel approach to male fertility by machine learning highlights a hidden link between haematological and spermatogenetic cells
Authors: Santi Daniele , Spaggiari Giorgia , Casonati Andrea , Casarini Livio , Grassi Roberto , Vecchi Barbara , Roli Laura , De Santis Maria Cristina , Orlando Giovanna , Gravotta Enrica , Baraldi Enrica , Setti Monica , Trenti Tommaso , Simoni Manuela
Published: May 2020

Background

Male infertility represents a complex clinical condition requiring an accurate multilevel assessment, in which machine learning technology, combining large data series in non‐linear and highly interactive ways, could be innovatively applied.

Methods

A longitudinal, observational, retrospective, big data study was carried out, applying for the first time the ML in the context of male infertility. A large database including all semen samples collected between 2010 and 2016 was generated, together with blood biochemical examinations, environmental temperature and air pollutants exposure. First, the database was analysed with principal component analysis and multivariable linear regression analyses. Second, classification analyses were performed, in which patients were a priori classified according to semen parameters. Third, machine learning algorithms were applied in a training phase (80% of the entire database) and in a tuning phase (20% of the data set). Finally, conventional statistical analyses were applied considering semen parameters and those other variables extracted during machine learning.

Results

The final database included 4239 patients, aggregating semen analyses, blood and environmental parameters. Classification analyses were able to recognize oligozoospermic, teratozoospermic, asthenozoospermic and patients with altered semen parameters (0.58 accuracy, 0.58 sensitivity and 0.57 specificity). Machine learning algorithms detected three haematological variables, that is lymphocytes number, erythrocyte distribution and mean globular volume, significantly related to semen parameters (0.69 accuracy, 0.78 sensitivity and 0.41 specificity).

Conclusion

This is the first machine learning application to male fertility, detecting potential mathematical algorithms able to describe patients' semen characteristics changes. In this setting, a possible hidden link between testicular and haematopoietic tissues was suggested, according to their similar proliferative properties.
Pension Funding Regulations and Actuarial Gains and Losses
Authors: Heo Kyongsun , Pae Jinhan
Published: May 2020

With pervasive pension funding deficits, Korean firms have been under pressure to improve their funding levels. We examine whether firms have incentives to set obligation‐decreasing pension assumptions when they have large pension deficits (pension obligations in excess of plan assets) and when they make insufficient contributions to external pension funds. We find that firms report larger actuarial gains (or smaller actuarial losses) associated with the remeasurement of pension liabilities when their pension funding ratio (the ratio of the fair value of plan assets to defined benefit obligations) is lower and when contributions to plan assets relative to pension service costs are smaller. Next, upon the introduction of a minimum pension funding guideline, we find that the effect of the funding ratio and contributions to pension funds on actuarial gains and losses is more pronounced for firms whose funding ratios are slightly below the minimum funding ratio than it is for firms whose funding ratios exceed or fall short of the minimum by a large margin. Our results indicate that firms opportunistically exercise discretion regarding corporate pension accounting under International Financial Reporting Standards to comply with pension funding regulations, thereby reducing perceived pension deficits.
Multimodal learning analytics to investigate cognitive load during online problem solving
Authors: Larmuseau Charlotte , Cornelis Jan , Lancieri Luigi , Desmet Piet , Depaepe Fien
Published: May 2020

To have insight into cognitive load (CL) during online complex problem solving, this study aimed at measuring CL through physiological data. This study experimentally manipulated intrinsic and extraneous load of exercises in the domain of statistics, resulting in four conditions: high complex with hints, low complex with hints, high complex without hints and low complex without hints. The study had a within‐subject‐design in which 67 students solved the exercises in a randomized order. Self‐reported CL was combined with physiological data, namely, galvanic skin response (GSR), skin temperature (ST), heart rate (HR) and heart rate variability (HRV). Multiple imputation was used for handling missing data from resp. 16 and 19 students for GSR/ST and HR/HRV. First, differences between conditions in view of physiological data were examined. Second, we investigated how much variance of self‐reported CL and task performance was explained by physiological data. Finally, we investigated which features can be used to assess (objective) CL. Results revealed no significant differences between the manipulated conditions in terms of physiological data. Nonetheless, HR and ST were significantly related to self‐reported CL, whereas ST to task performance. Additionally, this study revealed the potential of ST and HR to assess high CL.
Misperceptions of opposite‐sex preferences for thinness and muscularity
Authors: Lei Xue , Perrett David
Published: May 2020

Thin and muscular have been characterized as ideals for women and men, respectively. Little research has investigated whether men and women have accurate perceptions of opposite‐sex preferences of thinness and muscularity. Further, no study has explored whether opposite‐sex perceptions of thinness and muscularity preferences differ for short‐term and long‐term relationships. The present study set out to address these questions. We used interactive 3D human models to represent bodies varying in size (body mass index/BMI weight scaled by height) and body composition. University‐aged (18–31) White European heterosexual men and women were asked to choose their own and ideal body shape, the ideal body shape for a short‐ and a long‐term partner, and the body shape they thought the opposite‐sex would most like for short‐ and long‐term partners. Women overestimated the thinness that men prefer in a partner and men overestimated the heaviness and muscularity that women prefer in a partner. These misperceptions were more exaggerated for short‐term relationships than for long‐term relationships. The results illustrate the importance of investigating misperceptions of opposite‐sex preferences and raise the possibility that correcting misperceptions might have utility in reducing body dissatisfaction or eating disorders.
Hepatic C9 cells switch their behaviour in short or long exposure to soft substrates
Authors: Cabriales Lucia , Hautefeuille Mathieu , Vázquez‐Victorio Genaro , Martinez‐Pastor David , Carretero‐Ortega Jorge , Jiménez‐Escobar Alejandra , Macias‐Silva Marina
Published: May 2020

Background Information

There have been several studies to understand the influence of stiffness of the culture substrates for different types of adherent cells. It is generally accepted that cell proliferation, spreading and focal adhesions increase with higher matrix stiffness. However, what remains unclear is whether this kind of cell behaviour may be reverted by culturing on soft substrates those cell lines that were originally selected or primed on stiff surfaces.

Results

Here, we studied the influence of substrate softness on proliferation, adhesion and morphology of the highly proliferative hepatic C9 cell line. We cultured C9 cells on soft and stiff polydimethylsiloxane (PDMS) substrates prepared with two different elastic moduli in the range of 10 and 200 kPa, respectively. Lower cell proliferation was observed on substrates with lower stiffness without affecting cell viability. The proliferation rate of C9 cell line along with extracellular growth‐regulated kinase (ERK) phosphorylation was decreased on soft PDMS. Despite this cell line has been described as a hepatic epithelial cell, our characterisation demonstrated that the origin of C9 cells is uncertain, although clearly epithelial, with the expression of markers of several hepatic cells. Surprisingly, consecutive passages of C9 cells on soft PDMS did not alter this mesenchymal phenotype, vimentin expression did not decrease when culturing cells in soft substrates, even though the ERK phosphorylation levels eventually were increased after several passages on soft PDMS, triggering again an increase of cell proliferation.

Conclusions and Significance

This study shows that the exposure of C9 cells to soft substrates promoted a decrease of cell proliferation rate, as reported for other types of cells on PDMS, whereas a much longer term exposure caused cells to adapt to softness after trained for several passages, reactivating proliferation. During this phenomenon, the morphology and phenotype of trained cells was modified accompanying the increase of cell proliferation rate contrary to the effect observed in short periods of cell culture. In contrast to previous reports, cell death was not observed during these experiments, discarding a cell selection mechanism and suggesting soft cell adaptation may be limited in time in C9 cells.
Regulation of gene expression by MF63, a selective inhibitor of microsomal PGE synthase 1 (mPGES1) in human osteoarthritic chondrocytes
Authors: Tuure Lauri , Pemmari Antti , Hämäläinen Mari , Moilanen Teemu , Moilanen Eeva
Published: May 2020

Background and Purpose

mPGES1 catalyses the production of PGE2, the most abundant prostanoid related to inflammation and pain in arthritis. mPGES1 is suggested to be a safer and more selective drug target in inflammatory conditions compared to the COX enzymes inhibited by NSAIDs. In the present study, we investigated the effects of the selective mPGES1 inhibitor MF63 on gene expression in primary human chondrocytes from patients with osteoarthritis (OA).

Experimental Approach

Chondrocytes were isolated from articular cartilage obtained from osteoarthritis patients undergoing knee replacement surgery. The effects of MF63 were studied in the primary chondrocytes with RNA‐sequencing based genome‐wide expression analysis. The main results were confirmed with qRT‐PCR and compared with the effects of the NSAID ibuprofen. Functional analysis was performed with the GO database and interactions between the genes were studied with STRING.

Key Results

MF63 enhanced the expression of multiple metallothionein 1 (MT1) isoforms as well as endogenous antagonists of IL‐1 and IL‐36. The expression of IL‐6, by contrast, was down‐regulated. These genes were also essential in functional and interaction network analyses. The effects of MF63 were consistent in qRT‐PCR analysis, whereas the effects of ibuprofen overlapped only partly with MF63. There were no evident findings of catabolic effects by MF63.

Conclusion and Implications

Metallothionein 1 has been suggested to have anti‐inflammatory and protective effects in cartilage. Up‐regulation of the antagonists of IL‐1 superfamily and down‐regulation of the pro‐inflammatory cytokine IL‐6 also support novel anti‐inflammatory and possibly disease‐modifying effects of mPGES1 inhibitors in arthritis.
Dietary importance of C3 and CAM food pathways for birds in a Neotropical semiarid zone
Authors: González‐Carcacía José Antonio , Herrera M. L. Gerardo , Nassar Jafet M.
Published: May 2020

Vegetation of tropical dry ecosystems is represented by patches of plants with different photosynthetic pathways. We used C and N stable isotope mixing models to assess the relative importance of CAM and C3 vegetation as direct or indirect sources of food for birds in a Neotropical semiarid zone. We analyzed tissues from 26 bird species encompassing a broad array of feeding habits in the dry and rainy seasons. Although CAM plants are important elements of our study site, their use as food was mainly restricted to some plant‐eating and omnivorous bird species. “Intermediate” or “High” dependence on CAM food was observed in only 7 species: three frugivores, one nectarivore, one granivore, and two omnivores. Instead, C3‐derived food sustained most of the bird species studied, even some for which dependence on CAM‐derived food was reported in studies using other methodological approaches. Consumption of C3 insects extended to the entire assemblage of birds, including plant‐eating species. Our findings highlight the importance of maintaining vegetation heterogeneity in arid zones for animal communities and the need to provide increasing protection measures to woody C3 species, as their local demand for firewood is rapidly increasing.

Abstract in Spanish is available with online material.
‘What is left…?’: The implications of losing Maintained Nursery Schools for vulnerable children and families in England
Authors: Solvason Carla , Webb Rebecca , Sutton‐Tsang Samantha
Published: May 2020

This TACTYC funded research highlights the role that Maintained Nursery Schools (MNS) play in supporting families within areas of extreme social deprivation in the UK. Data collected through survey and interview demonstrated the positive impact that these schools have upon disadvantaged children and their families, providing a breadth and depth of ongoing care, against a backdrop of ongoing fiscal cuts and uncertainty. Often this provision was in lieu of the reported minimisation of other social services support for struggling families. We argue in this paper that the loss of these state institutions could be highly detrimental to the families that they currently support.
Moral Values Reveal the Causality Implicit in Verb Meaning
Authors: Niemi Laura , Hartshorne Joshua , Gerstenberg Tobias , Stanley Matthew , Young Liane
Published: May 2020

Prior work has found that moral values that build and bind groups—that is, the binding values of ingroup loyalty, respect for authority, and preservation of purity—are linked to blaming people who have been harmed. The present research investigated whether people's endorsement of binding values predicts their assignment of the causal locus of harmful events to the victims of the events. We used an implicit causality task from psycholinguistics in which participants read a sentence in the form “SUBJECT verbed OBJECT because…” where male and female proper names occupy the SUBJECT and OBJECT position. The participants were asked to predict the pronoun that follows “because”—the referent to the subject or object—which indicates their intuition about the likely cause of the event. We also collected explicit judgments of causal contributions and measured participants' moral values to investigate the relationship between moral values and the causal interpretation of events. Using two verb sets and two independent replications (N = 459, 249, 788), we found that greater endorsement of binding values was associated with a higher likelihood of selecting the object as the cause for harmful events in the implicit causality task, a result consistent with, and supportive of, previous moral psychological work on victim blaming. Endorsement of binding values also predicted explicit causal attributions to victims. Overall, these findings indicate that moral values that support the group rather than the individual reliably predict that people shift the causal locus of harmful events to those affected by the harms.