bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ancient origins of complex neuronal genes
Authors: McCoy Matthew J. , Fire Andrew Z. 
Published: March 2023

AbstractHow nervous systems evolved is a central question in biology. An increasing diversity of synaptic proteins is thought to play a central role in the formation of specific synapses leading to nervous system complexity. The largest animal genes, often spanning millions of base pairs, are known to be enriched for expression in neurons at synapses and are frequently mutated or misregulated in neurological disorders and diseases. While many of these genes have been studied independently in the context of nervous system evolution and disease, general principles underlying their parallel evolution remain unknown. To investigate this, we directly compared orthologous gene sizes across eukaryotes. By comparing relative gene sizes within organisms, we identified a distinct class of large genes with origins predating the diversification of animals and in many cases the emergence of dedicated neuronal cell types. We traced this class of ancient large genes through evolution and found orthologs of the large synaptic genes driving the immense complexity of metazoan nervous systems, including in humans and cephalopods. Moreover, we found that while these genes are evolving under strong purifying selection as demonstrated by low dN/dS scores, they have simultaneously grown larger and gained the most isoforms in animals. This work provides a new lens through which to view this distinctive class of large and multi-isoform genes and demonstrates how intrinsic genomic properties, such as gene length, can provide flexibility in molecular evolution and allow groups of genes and their host organisms to evolve toward complexity.
Automatic sleep staging by a hybrid model based on deep 1D-ResNet-SE and LSTM with single-channel raw EEG signals
Authors: Li Weiming , Gao Junhui 
Published: March 2023

AbstractSleep staging is crucial in assessing sleep quality and diagnosing sleep disorders. Recent advances in deep learning methods with electroencephalogram (EEG) signals have shown remarkable success in automatic sleep staging. However, the use of deeper neural networks may lead to the issues of gradient disappearance and explosion, while the non-stationary nature and low signal-to-noise ratio of EEG signals can negatively impact feature representation. To overcome these challenges, we proposed a novel lightweight sequence-to-sequence deep learning model, 1D-ResNet-SE-LSTM, to classify sleep stages into five classes using single-channel raw EEG signals. Our proposed model consists of two main components: a one-dimensional residual convolutional neural network with a squeeze-and-excitation module to extract and reweight features from EEG signals, and a long short-term memory network to capture the transition rules among sleep stages. In addition, we applied the weighted cross-entropy loss function to alleviate the class imbalance problem. We evaluated the performance of our model on two publicly available datasets, Sleep-EDF Expanded and ISRUC-Sleep, and obtained an overall accuracy rate of 86.39% and 81.97%, respectively, along with corresponding macro average F1-scores of 81.95% and 79.94%. Our model outperforms existing sleep staging models, particularly for the N1 stage, where it achieves F1-scores of 59.00% and 55.53%. The kappa coefficient is 0.812 and 0.766 for the Sleep-EDF Expanded and ISRUC-Sleep datasets, respectively, indicating strong agreement with certified sleep experts. We also investigated the effect of different weight coefficient combinations and sequence lengths of EEG epochs used as input to the model on its performance. Furthermore, the ablation study was conducted to evaluate the contribution of each component to the model’s performance.
Morphogen-driven human iPSCs differentiation in 3Din vitromodels of gastrulation is precluded by physical confinement
Authors: Alsehli Haneen S. , Roy Errin , Williams Thomas , Kuziola Alicja , Guo Yunzhe , Green Jeremy , Gentleman Eileen , Danovi Davide 
Published: March 2023

AbstractIn early human development, gastrulation is tightly associated with lineage specification. The interplay between mechanical forces and biochemical signals during these processes is poorly understood. Here, we dissect the effects of biochemical cues and physical confinement on a 3D in vitro model of gastrulation that uses spheroids formed from human induced pluripotent stem cells (hiPSCs). First, we compare self-renewing versus differentiating media conditions in free-floating cultures, and observe the emergence of organised tri-germ layers. In these unconfined cultures, BMP4 exposure induces polarised expression of SOX17 in conjunction with spheroid elongation. We then physically confine spheroids using PEG-peptide hydrogels and observe dramatically reduced SOX17 expression, albeit rescued if gels that soften over time are used instead. Our study combines high-content imaging, synthetic hydrogels and hiPSCs-derived models of early development to define the drivers causing changes in shape and emergence of germ layers.
Digital transformation in tourism: bibliometric literature review based on machine learning approach
Authors: Madzík Peter , Falát Lukáš , Copuš Lukáš , Valeri Marco 
Published: March 2023

PurposeThis bibliometric study provides an overview of research related to digital transformation (DT) in the tourism industry from 2013 to 2022. The goals of the research are as follows: (1) to identify the development of academic papers related to DT in the tourism industry, (2) to analyze dominant research topics and the development of research interest and research impact over time and (3) to analyze the change in research topics during the pandemic.Design/methodology/approachIn this study, the authors processed 3,683 papers retrieved from the Web of Science and Scopus. The authors performed different types of bibliometric analyses to identify the development of papers related to DT in the tourism industry. To reveal latent topics, the authors implemented topic modeling based on latent Dirichlet allocation with Gibbs sampling.FindingsThe authors identified eight topics related to DT in the tourism industry: City and urban planning, Social media, Data analytics, Sustainable and economic development, Technology-based experience and interaction, Cultural heritage, Digital destination marketing and Smart tourism management. The authors also identified seven topics related to DT in the tourism industry during the Covid-19 pandemic; the largest ones are smart analytics, marketing strategies and sustainability.Originality/valueTo identify research topics and their development over time, the authors applied a novel methodological approach – a smart literature review. This machine learning approach is able to analyze a huge amount of documents. At the same time, it can also identify topics that would remain unrevealed by a standard bibliometric analysis.
Day-of-the-week effect and volatility in stock returns: evidence from the Indian stock market
Authors: Aggarwal Khushboo , Jha Mithilesh Kumar 
Published: March 2023

PurposeThe purpose of this paper is to examine the existence of the day-of-the-week effect in the Indian stock market.Design/methodology/approachGeneralized Autoregressive Conditional Heteroskedasticity (GARCH) (1, 1), Exponential GARCH (EGARCH) (1, 1) and Threshold GARCH (TGARCH) (1, 1) models are employed to examine the day-of-the-week effect in the Indian stock market for the period of 28 years from 3rd July, 1990 to 31st March, 2022.FindingsThe empirical results derived from the GARCH models indicate the existence of day-of-the-week effects on stock returns and volatility of the Indian stock market. The study reveals that all the days of the week are positive and significant in National Stock Exchange (NSE)-Nifty market returns. The findings confirm the persistence of ARCH and GARCH effects in the daily return series. Moreover, the asymmetric GARCH models show that the daily stock returns exhibit significant asymmetric (leverage) effects.Practical implicationsThe results of this study established that the Indian stock market is not efficient and there exists an opportunity to the traders for predicting the future prices and earning abnormal profits in the Indian stock market. The findings of the study are important for traders, investors and portfolio managers to earn abnormal returns by cross-border diversification.Originality/valueFirst, to the best of the authors' knowledge, this paper is the first to study the day-of-the-week effect in Indian stock market considering the most recent and longer time period (1990–2022). Second, unlike previous research, this study used GARCH models (GARCH, EGARCH and TGARCH) to capture the volatility clustering in the data.
Brand equity chain and brand equity measurement approaches
Authors: Oliveira Marta Olivia Rovedder de , Heldt Rodrigo , Silveira Cleo Schmitt , Luce Fernando Bins 
Published: March 2023

PurposeAlthough brand equity (BE) is a widely accepted concept, its definition is still elusive, and researchers have not reached a consensus about which measures provide the best estimates of this complex and multi-faceted construct. Hence, the authors propose a BE chain that incorporates consumer-based BE (CBBE) and firm-based BE (FBBE) measurement approaches, advocating in favor of a holistic approach and encouraging theoretical and empirical studies that assess the BE chain.Design/methodology/approachThe methodology entailed an extensive literature review on the subject. The authors included many different sources and the most accepted ones for measuring CBBE and FBBE.FindingsThe authors present 10 propositions to build the BE chain, encompassing the different approaches of BE and including its antecedents and consequences.Originality/valueConceptualizing BE is a complex problem given the different viewpoints describing several aspects of this intangible marketing asset. Thus, this study aims to foster discussions about such viewpoints and provide a framework to support the sedimentation of BE conceptualization.
Drivers of gated community developments in Ghana: perspective of developers
Authors: Otchere Gideon Kwame , Mintah Kwabena , Callanan Judith 
Published: March 2023

PurposeGated communities continue to spread in popularity across cities around the world. Ghana has seen considerable growth in the development of gated communities over the last few years. This phenomenon manifests in the majority new residential developments and most forms of residential property advertisement in the capital city. The purpose of this paper is to explore the drivers of gated community developments in Ghana from the perspective of gated community developers.Design/methodology/approachThis paper used a qualitative research approach. Through face-to-face semi-structured interviews, data was collected from purposively selected key stakeholders in the gated community development market, including developers, managers and consultants.FindingsThe drivers identified from the developers' perspective were the demand for gated community properties, the control over and ease of management of assets and interests, the high development/production cost of real estate and speculative development of gated community properties.Originality/valueThis paper is an initial study that explores the drivers of gated community developments in Ghana from the perspective of gated community developers. This paper extends the literature on gated communities beyond the residents perspective.
Study on the anti‐inflammatory effect of stachyose by inhibiting TLR4/NF‐κB signalling pathway in vitro and in vivo
Authors: Jiang Songsong , Li Qian , Han Shiwen , Wang Hengpeng , Tang Xinlei , Wang Tao , Meng Xiangren 
Published: March 2023

AbstractThis study aimed to explore the anti‐inflammatory effect of stachyose, a tetrasaccharide extracted from Stachys sieboldii Miq. A lipopolysaccharide (LPS)‐stimulated RAW264.7 macrophages model and a dextran sodium sulfate (DSS)‐induced ulcerative colitis BALB/C mice model was used to assess the anti‐inflammatory effect of stachyose both in vitro and in vivo. The levels of nitric oxide (NO) and cytokines (interleukin‐1β, interleukin‐6 and tumour necrosis factor‐α) were detected using enzyme‐linked immunosorbent assay methods; moreover, haematoxylin–eosin staining was used to observe changes in intestinal morphology of mice. In addition, the possible mechanisms were explored by reverse transcription‐polymerase chain reaction and western blot. Results showed that stachyose and four other oligosaccharides (galacto‐oligosaccharides, xylo‐oligosaccharides, inulin and resistant dextrin) inhibited NO secretion and the production of pro‐inflammatory cytokines in LPS‐stimulated RAW264.7 macrophages in a dose‐dependent manner, whereas stachyose was most effective in vitro. In mice, different doses of stachyose significantly alleviated the symptoms of DSS‐induced ulcerative colitis and stachyose also significantly inhibited the production of inflammatory cytokines and myeloperoxidase in vivo. In addition, our findings illustrated that stachyose inhibited expression of toll‐like receptor 4 (TLR4) and suppressed the phosphorylation of nuclear factor (NF)‐κB p65 both in vitro and in vivo. Taken together, results demonstrated that stachyose exerted anti‐inflammatory effect through inhibition of the TLR4/NF‐κB signalling pathway.
Eelgrass (Zostera spp.) associated phytomyxids are host‐specific congeneric parasites and predominant eukaryotes in the eelgrass rhizosphere on a global scale
Authors: Kolátková Viktorie , Mooney Megan , Kelly Kate , Hineva Elitsa , Gawryluk Ryan M. R. , Elliott Joel 
Published: March 2023

AbstractTogether with increasing environmental and anthropogenic pressures, pathogenic diseases are one of the important factors contributing to the ongoing decline of seagrass meadows worldwide; yet the diversity and ecology of the microorganisms acknowledged as seagrass parasites remain critically understudied. Here, we investigate phytomyxid parasites (Rhizaria: Endomyxa: Phytomyxea) of three different eelgrass (Zostera spp.) species found in the Northern hemisphere. We present molecular evidence that Plasmodiophora bicaudata, a long‐recognized parasite of dwarf eelgrass taxa, is closely related to the novel phytomyxid recently discovered in root hairs of Zostera marina, and together they form a distinct clade within the order Phagomyxida, proposed here as Feldmanniella gen. nov. A full life cycle is systematically described in a phagomyxid representative for the first time, proving its conformity with the generalized phytomyxid life history, despite previous uncertainties. The presence of primary infection stages in nearly all collected eelgrass specimens, and subsequent analysis of amplicon sequences from a global Z. marina dataset, reveal phytomyxids to be ubiquitous and one of the predominant microeukaryotes associated with eelgrass roots on a global scale. Our discoveries challenge the current view of Phytomyxea as rare entities in seagrass meadows and suggest their generally low pathogenicity in natural ecosystems.
Saying Yes without Yes: The Positive Response System in Latin
Authors: Potočnik Tomaž 
Published: March 2023

AbstractThe article studies a set of three positive response strategies in Latin: the echo response and the positive response particles ita and sic. It aims to determine their functions and division of labour and to establish what kind of agreement strategy existed in Latin, based on the typology of positive response systems by Sadock and Zwicky (1985). The main data for the study are drawn from the comedies of Plautus and Terence. Based on their position in an utterance, an attempt is made to determine whether the occurrences of ita and sic can be considered positive response particles, comparable to modern positive response particles, such as yes. By comparing the antecedents which trigger the response strategies studied here, it is shown that they are not interchangeable and that the echo response is the default positive response strategy, while ita and sic have a limited use, at least in the Latin of Plautus and Terence. The dynamic‐diachronic section shows that both the echo and non‐echo responses originate in the so‐called sentence answer.
A new Coffee Brewing Control Chart relating sensory properties and consumer liking to brew strength, extraction yield, and brew ratio
Authors: Guinard Jean‐Xavier , Frost Scott , Batali Mackenzie , Cotter Andrew , Lim Lik X. , Ristenpart William D. 
Published: March 2023

AbstractThe classic Coffee Brewing Control Chart (BCC) was originally developed in the 1950s. It relates coffee quality to brew strength and extraction yield, and it is still widely used today by coffee industry professionals around the world to provide guidance on the brewing of coffee. Despite its popularity, recent experimental studies have revealed that sensory attributes and consumer preferences actually follow much more complicated trends than those indicated by the classic BCC. Here, we present a methodology to synthesize the results of these recent studies on drip‐brewed coffee to generate new versions of the BCC: a new Sensory BCC that displays a broad array of statistically significant sensory attributes across typical total dissolved solids and percent extraction ranges, a new Consumer BCC that highlights the existence of two preference clusters with different likes and dislikes across those ranges, a new Sensory and Consumer BCC that combines both sensory descriptive and consumer preferences on the same chart, and a more streamlined BCC that omits consumer preferences and focuses on the overarching sensory descriptive trends. The new BCCs provide more accurate insight on how best to brew coffee to achieve desired sensory profiles.Practical ApplicationThrough the manipulation of yield and extraction parameters, the new Sensory and Consumer Coffee Brewing Control Chart presented here can be used by brewers of drip coffee to design coffees with specific sensory profiles and match the preferences of different consumer types.
Long‐term endoscopic surveillance in HBV compensated cirrhotic patients treated with Tenofovir or Entecavir for 11 years
Authors: Farina Elisa , Loglio Alessandro , Tosetti Giulia , Degasperi Elisabetta , Viganò Mauro , Gentile Carmine , Monico Sara , Perbellini Riccardo , Borghi Marta , Facchetti Floriana , Uceda Renteria Sara Colonia , Ceriotti Ferruccio , Cerini Federica , Primignani Massimo , Lampertico Pietro 
Published: March 2023

SummaryBackgroundLong‐term administration of TDF/ETV in patients with HBV‐related compensated cirrhosis reduces HCC and decompensation events but the effect of this regimen on development/regression of oesophageal varices (EV) is currently unknown.AimTo assess the risk of EV development/progression in this population.MethodsA total of 186 Caucasian HBV‐monoinfected compensated cirrhotics were enrolled in a long‐term cohort study from TDF/ETV introduction. Upper GI endoscopies were performed according to Baveno recommendations. Primary endpoint was development/progression of oesophageal/gastric varices over time.ResultsAt TDF/ETV start, median age was 61 years, 80% males, 60% HBV‐DNA undetectable, 63% NUCs previously exposed, 73% normal ALT, 40% platelets <150,000/mmc and 25 (13%) with low‐risk varices (LRV). During 11 years of antiviral therapy and 666 endoscopies performed, 9 patients either developed or had a progression of oesophageal or gastric varices with an 11‐year cumulative probability of 5.1% (95% CI 3–10%); no patient bled. Out of 161 patients without EV at baseline, the 11‐year probably was 4.5% with all varices developing within the first six years of treatment. In 25 patients with LRV at baseline, the 11‐year probability of progression or regression was 9.3% and 58%, respectively. Only baseline platelet count (HR 0.96, p = 0.028) was associated with LRV development at multivariate analysis: platelet ≤90,000/mmc (AUROC 0.70) had 98.1% specificity, 42.9% sensitivity, 50% PPV for LRV onset.ConclusionsIn compensated cirrhotic patients under long‐term effective TDF/ETV treatment, the 11‐year risk of developing/progressing EV is negligible, thus challenging the current endoscopic surveillance recommendations in patients without EV at baseline.
Estimation of Time-Specific Intervention Effects on Continuously Distributed Time-to-Event Outcomes by Targeted Maximum Likelihood Estimation
Authors: Rytgaard Helene C. W. , Eriksson Frank , van der Laan Mark J. 
Published: March 2023

AbstractThis work considers targeted maximum likelihood estimation (TMLE) of treatment effects on absolute risk and survival probabilities in classical time-to-event settings characterized by right-censoring and competing risks. TMLE is a general methodology combining flexible ensemble learning and semiparametric efficiency theory in a two-step procedure for substitution estimation of causal parameters. We specialize and extend the continuous-time TMLE methods for competing risks settings, proposing a targeting algorithm that iteratively updates cause-specific hazards to solve the efficient influence curve equation for the target parameter. As part of the work, we further detail and implement the recently proposed highly adaptive lasso estimator for continuous-time conditional hazards with L1-penalized Poisson regression. The resulting estimation procedure benefits from relying solely on very mild nonparametric restrictions on the statistical model, thus providing a novel tool for machine-learning-based semiparametric causal inference for continuous-time time-to-event data. We apply the methods to a publicly available dataset on follicular cell lymphoma where subjects are followed over time until disease relapse or death without relapse. The data display important time-varying effects that can be captured by the highly adaptive lasso. In our simulations that are designed to imitate the data, we compare our methods to a similar approach based on random survival forests and to the discrete-time TMLE.