bluuebunny/crossref_metadata_2025_split huggingface dataset:
Unexpected genetic and microbial diversity for arsenic cycling in deep sea cold seep sediments
Authors: Zhang Chuwen , Liu Xinyue , Shi Ling-Dong , Li Jiwei , Xiao Xi , Shao Zongze , Dong Xiyang 
Published: November 2022

AbstractCold seeps, where cold hydrocarbon-rich fluid escapes from the seafloor, showed strong enrichment of toxic metalloid arsenic (As). The toxicity and mobility of As can be greatly altered by microbial processes that play an important role in global As biogeochemical cycling. However, a global overview of genes and microbes involved in As transformation at seeps remains to be fully unveiled. Using 87 sediment metagenomes and 33 metatranscriptomes derived from 13 globally distributed cold seeps, we show that As detoxification genes (arsM, arsP, arsC1/arsC2,acr3) were prevalent at seeps and more phylogenetically diverse than previously expected. Asgardarchaeota and a variety of unidentified bacterial phyla (e.g. 4484-113, AABM5-125-24 and RBG-13-66-14) may also function as the key players in As transformation. The abundances of As-cycling genes and the compositions of As-associated microbiome shifted across different sediment depths or types of cold seep. The energy-conserving arsenate reduction or arsenite oxidation could impact biogeochemical cycling of carbon and nitrogen, via supporting carbon fixation, hydrocarbon degradation and nitrogen fixation. Overall, this study provides a comprehensive overview of As-cycling genes and microbes at As-enriched cold seeps, laying a solid foundation for further studies of As cycling in deep sea microbiome at the enzymatic and processual levels.
A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers
Authors: Singh Gagandeep , Alser Mohammed , Denolf Kristof , Firtina Can , Khodamoradi Alireza , Cavlak Meryem Banu , Corporaal Henk , Mutlu Onur 
Published: November 2022

AbstractNanopore sequencing generates noisy electrical signals that need to be converted into a standard string of DNA nucleotide bases using a computational step called basecalling. The performance of basecalling has critical implications for all later steps in genome analysis. Therefore, there is a need to reduce the computation and memory cost of basecalling while maintaining accuracy. We presentRUBICON, a framework to develop efficient hardware-optimized basecallers. We demonstrate the effectiveness ofRUBICONby developingRUBICALL, the first hardware-optimized mixed-precision basecaller that performs efficient basecalling, outperforming the state-of-the-art basecallers. We believeRUBICONoffers a promising path to develop future hardware-optimized basecallers.
A simple framework for agent-based modeling with extracellular matrix
Authors: Metzcar John , Duggan Ben S. , Fischer Brandon , Murphy Matthew , Heiland Randy , Macklin Paul 
Published: November 2022

AbstractExtracellular matrix (ECM) is a key component of the cellular microenvironment and critical in multiple disease and developmental processes. Representing ECM and cell-ECM interactions is a challenging multiscale problem as they span molecular-level details to tissue-level dynamics. While several computational frameworks exist for ECM modeling, they often focus on very detailed modeling of individual ECM fibers or represent only a single aspect of the ECM. Using the PhysiCell agent-based modeling platform, we developed a framework of intermediate detail with the ability to capture bidirectional cell-ECM interactions. We represent a small region of ECM, an ECM element, with three variables describing its local microstructure: anisotropy, density, and overall fiber orientation. To spatially model the ECM, we use an array of ECM elements. Cells remodel local ECM microstructure and in turn, local microstructure impacts cellular motility. We demonstrate the utility of this framework and reusability of its core cell-ECM interaction model through examples in cellular invasion, wound healing, basement membrane degradation, and leader-follower collective migration. Despite the relative simplicity of the framework, it is able to capture a broad range of cell-ECM interactions of interest to the modeling community. Furthermore, variables representing the ECM microstructure are accessible through simple programming interfaces. This allows them to impact cell behaviors, such as proliferation and death, without requiring custom code for each interaction, particularly through PhysiCell’s modeling grammar, enabling rapid modeling of a diverse range of cell-matrix biology. We make this framework available as a free and open source software package athttps://github.com/PhysiCell-Models/collective-invasion.
SMARCB1 loss creates patient-specificMYCtopologies that drive malignant rhabdoid tumor growth
Authors: Liu Ning Qing , Paassen Irene , Custers Lars , Teunissen Hans , Ayyildiz Dilara , He Jiayou , Hoving Eelco W. , de Wit Elzo , Drost Jarno 
Published: November 2022

AbstractMalignant rhabdoid tumor (MRT) is a highly malignant and often lethal childhood cancer. MRTs are genetically defined by bi-allelic inactivating mutations inSMARCB1, a member of the BRG1/BRM-associated factors (BAF) chromatin remodeling complex. Mutations in BAF complex members are common in human cancer, yet their contribution to tumorigenesis remains in many cases poorly understood. Here, we studied derailed regulatory landscapes as a consequence ofSMARCB1loss in the context of MRT. Our multi-omics approach on patient-derived MRT organoids revealed a dramatic reshaping of the regulatory landscape uponSMARCB1reconstitution. Chromosome conformation capture experiments subsequently revealed patient-specific looping of distal enhancer regions with the promoter of theMYConcogene. This intertumoral heterogeneity inMYCenhancer utilization is also present in patient MRT tissues as shown by combined single-cell RNA-seq and ATAC-seq. We show that loss ofSMARCB1drives patient-specific epigenetic reprogramming underlying MRT tumorigenesis.
Flow cytometry-based biomarker assay forin vitroidentification of heat tolerance conferring coral symbionts
Authors: Buerger Patrick , Buler Marcin , Yeap Heng Lin , Edwards Owain R , van Oppen Madeleine JH , Oakeshott John G , Court Leon 
Published: November 2022

ABSTRACTCorals’ tolerance to high temperature stress largely depends on their symbiotic microalgae (Symbiodiniaceae). However, the contributing microalgal traits are largely unclear. Here we compare thein vitrocellular profiles of sevenCladocopium C1acromicroalgal strains (derived from the same ancestral strain) during a four-week exposure to 27°C or 31°C. One was an unselected wild-type strain (WT), three were selected at 31°C for nine years and shown to confer thermal tolerance on the coral host (SS+) and three others were similarly selected but did not confer tolerance (SS-). Flow cytometry was used to measure the intracellular stress indicators reactive oxygen species (ROS), reduced glutathione (rGSH) and mitochondrial-membrane potential (ΔΨm), as well as cell size/shape and photosynthetic pigments. Cell densities and photosynthetic efficiency (ΦPSII, Fv/Fm) were also measured. WT showed the highest levels of intracellular ROS and ΔΨm, lowest rGSH and largest cell sizes at both temperatures. SS+ strains had the lowest ROS and highest rGSH values and a unique pattern of correlations among parameters at 31°C. Our results support previous reports implicating the role of microalgal ROS, ΔΨm and rGSH in holobiont thermal tolerance and suggest flow cytometry is a useful pre-screening tool for identifying microalgal strains with enhanced thermal tolerance.
An SNF2 helicase-like protein links mitotic transcription termination to sister chromatid resolution
Authors: Carmo Catarina , Coelho João , Silva Rui , Tavares Alexandra , Boavida Ana , Gaetani Paola , Martinho Rui Gonçalo , Oliveira Raquel A. 
Published: November 2022

AbstractMitotic chromatin is largely assumed incompatible with transcription due to changes in the transcription machinery and chromosome architecture. However, the mechanisms of mitotic transcriptional inactivation and their interplay with chromosome assembly remain largely unknown. By monitoring ongoing transcription inDrosophilaearly embryos, we reveal that eviction of nascent mRNAs from mitotic chromatin occurs after substantial chromosome compaction and is not promoted by condensin I. Instead, we show that the timely removal of transcripts from mitotic chromatin is driven by the SNF2 helicase-like protein Lodestar (Lds), identified here as a modulator of sister chromatid cohesion defects. In addition to transcriptional termination, we uncovered that Lds cooperates with Topoisomerase 2 to ensure efficient sister chromatid resolution and mitotic fidelity. We conclude that mitotic transcriptional termination is not a passive consequence of cell cycle progression and/or chromosome compaction but occurs via dedicated mechanisms with functional parallelisms to sister chromatid resolution.
Curli amyloid fibers inEscherichia colibiofilms: the influence of water availability on their structure and functional properties
Authors: Siri Macarena , Mangiarotti Agustín , Vázquez-Dávila Mónica , Bidan Cécile M. 
Published: November 2022

ABSTRACTE. colibiofilms consist of bacteria embedded in a self-produced matrix mainly made of protein fibers and polysaccharides. The curli amyloid fibers found in the biofilm matrix are promising versatile building blocks to design sustainable bio-sourced materials. To exploit this potential, it is crucial to understand i) how environmental cues during biofilm growth influence the molecular structure of these amyloid fibers, and ii) how this translates at higher length scales. To explore these questions, we studied the effect of water availability during biofilm growth on the conformation and functions of curli. We used microscopy and spectroscopy to characterize the amyloid fibers purified from biofilms grown on nutritive substrates with different water contents, and micro-indentation to measure the rigidity of the respective biofilms. The purified curli amyloid fibers present differences in the yield, structure and functional properties upon biofilm growth conditions. Fiber packing and β-sheets content correlate with their hydrophobicity and chemical stability, and with the rigidity of the biofilms. Our study highlights howE. colibiofilm growth conditions impact curli structure and functions contributing to macroscopic materials properties. These fundamental findings infer an alternative strategy to tune curli structure, which will ultimately benefit to engineer hierarchical and functional curli-based materials.Graphical Abstract
Nirmatrelvir treatment blunts the development of antiviral adaptive immune responses in SARS-CoV-2 infected mice
Authors: Fumagalli Valeria , Di Lucia Pietro , Ravà Micol , Marotta Davide , Bono Elisa , Grassi Stefano , Donnici Lorena , Cannalire Rolando , Stefanelli Irina , Ferraro Anastasia , Esposito Francesca , Pariani Elena , Inverso Donato , Montesano Camilla , Delbue Serena , Tramontano Enzo , De Francesco Raffaele , Summa Vincenzo , Guidotti Luca G. , Iannacone Matteo 
Published: November 2022

AbstractAlongside vaccines, antiviral drugs are becoming an integral part of our response to the SARS-CoV-2 pandemic. Nirmatrelvir – an orally available inhibitor of the 3-chymotrypsin-like cysteine protease – has been shown to reduce the risk of progression to severe COVID-19. However, the impact of nirmatrelvir treatment on the development of SARS-CoV-2-specific adaptive immune responses is unknown. Here, by using a mouse model of SARS-CoV-2 infection, we show that nirmatrelvir administration early after infection blunts the development of SARS-CoV-2-specific antibody and T cell responses. Accordingly, upon secondary challenge, nirmatrelvir-treated mice recruited significantly fewer memory T and B cells to the infected lungs and to mediastinal lymph nodes, respectively. Together, the data highlight a potential negative impact of nirmatrelvir treatment with important implications for clinical management and might help explain the virological and/or symptomatic relapse after treatment completion reported in some individuals.
The determinants of profitability in non-financial UK SMEs
Authors: Youssef Iman S. , Salloum Charbel , Al Sayah Maher 
Published: November 2022

Purpose
The purpose of this study is to examine determinants of profitability of non-financial firms listed small- and medium-sized enterprises (SMEs) in the UK from 2012 till 2020. It has been argued that profitability plays a key role in economic development and growth. Despite the important role that SMEs play in developed economies like UK, academic research into SMEs profitability determinants in developed countries is not extensive.

Design/methodology/approach
The methodologies used include dynamic panel data estimation techniques. Relationship of nine independent variables with profitability was examined. Two models are created using return on assets (ROA) and return on equity (ROE) as dependent variables. Size, age, efficiency, working capital, liquidity, leverage and volatility of the firm represent firm-specific independent variables. Two macroeconomic variables, namely, gross domestic product and inflation are also used as independent variables. Data obtained from Thomson Reuters Data Stream for 93 listed SMEs companies in the UK from 2012 to 2020. Fixed effects, random effects and generalized method of moments were used in data analysis.

Findings
All variables showed significant influence on profitability, except liquidity reflecting insignificant impact on profitability in two regression models conducted for 93 firms under study. Efficiency, liquidity and leverage are the only three independent variables with similar impact on both ROA and ROE.

Practical implications
Identifying determinants of profitability will help stakeholders and corporate executive make sound decisions to ensure sustainability and stability at the firm level. This is particularly important given the key role played by SMEs in economic development and growth. The findings of this study would help direct financial management practices to ensure a favorable sustainable organizational performance.

Originality/value
This study differs from previous studies that focused mainly on developing countries; with limited research conducted on profitability of SMEs in developed economies. To the best of the author’s knowledge, this is the first study to examine factors influencing profitability of SMEs in UK. Previous studies concentrated on service sector like insurance and hotel firms.
An investigation of how stakeholders influence construction project performance: a small and medium sized contractor’s perspective in the Jordanian construction industry
Authors: Alkilani Suhair , Loosemore Martin 
Published: November 2022

PurposeThis research uses contingency theory and Venkatraman’s concept of moderating fit to explore how key project stakeholders (clients, consultants and suppliers) influence project performance from the perspective of small and medium contractors in the Jordanian construction industry.Design/methodology/approachAn anonymous structured survey was performed comprising 200 key informants including senior project managers, construction managers, engineers and general managers working for small- and medium-sized contractors in the Jordanian construction industry. The Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to analyse the data.FindingsThe results of this study show that consultant-related factors (quality of documentation produced, ability to communicate and technical competencies) are perceived to have the most significant direct effect on project performance, followed by client-related factors (payment promptness, decision certainty and documentation control) and supplier-related factors (supplier performance, defects control and logistics management).Originality/valueThe results contribute new theoretical, empirical and practical insights to existing construction project performance research by highlighting the key performance factors which need to be managed for each stakeholder group to ensure effective project performance from a small- and medium-sized contractor perspective.
Development and comparative of a new meta-ensemble machine learning model in predicting construction labor productivity
Authors: Karatas Ibrahim , Budak Abdulkadir 
Published: November 2022

PurposeThe study is aimed to compare the prediction success of basic machine learning and ensemble machine learning models and accordingly create novel prediction models by combining machine learning models to increase the prediction success in construction labor productivity prediction models.Design/methodology/approachCategorical and numerical data used in prediction models in many studies in the literature for the prediction of construction labor productivity were made ready for analysis by preprocessing. The Python programming language was used to develop machine learning models. As a result of many variation trials, the models were combined and the proposed novel voting and stacking meta-ensemble machine learning models were constituted. Finally, the models were compared to Target and Taylor diagram.FindingsMeta-ensemble models have been developed for labor productivity prediction by combining machine learning models. Voting ensemble by combining et, gbm, xgboost, lightgbm, catboost and mlp models and stacking ensemble by combining et, gbm, xgboost, catboost and mlp models were created and finally the Et model as meta-learner was selected. Considering the prediction success, it has been determined that the voting and stacking meta-ensemble algorithms have higher prediction success than other machine learning algorithms. Model evaluation metrics, namely MAE, MSE, RMSE and R2, were selected to measure the prediction success. For the voting meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R2 are 0.0499, 0.0045, 0.0671 and 0.7886, respectively. For the stacking meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R2 are 0.0469, 0.0043, 0.0658 and 0.7967, respectively.Research limitations/implicationsThe study shows the comparison between machine learning algorithms and created novel meta-ensemble machine learning algorithms to predict the labor productivity of construction formwork activity. The practitioners and project planners can use this model as reliable and accurate tool for predicting the labor productivity of construction formwork activity prior to construction planning.Originality/valueThe study provides insight into the application of ensemble machine learning algorithms in predicting construction labor productivity. Additionally, novel meta-ensemble algorithms have been used and proposed. Therefore, it is hoped that predicting the labor productivity of construction formwork activity with high accuracy will make a great contribution to construction project management.
The impact of different types of service robots usage in hotels on guests’ intention to stay
Authors: Alma Çallı Büşra , Çallı Levent , Sarı Çallı Didar , Çallı Fatih 
Published: November 2022

Purpose
The purpose of this study is to examine how consumers perceive the importance of using robot technologies for 12 services evaluated under two categories considering the technology acceptance model (TAM).

Design/methodology/approach
The conceptual model analysis used structural equation modeling with the partial least squares estimation method, considering 638 responses.

Findings
The results revealed that the perceived importance (PI) of robotic service delivery tasks under “room division” and “food and beverage and secondary services” affect perceived usefulness (PU) and perceived ease of use (PEOU) differently. Besides, PEOU and PU significantly influence attitudes toward using robot-staffed hotels.

Research limitations/implications
The nonprobability convenience sampling method was used as the data collection method. Future studies that prefer probabilistic methods will open a different perspective for evaluating the results.

Practical implications
This study’s empirical findings reveal which robot-delivered services are found significant by the customers and contribute to increased customer satisfaction and loyalty. In addition, it guides accurate demand and investment planning for the tourism and hospitality industry in the post-COVID-19 era.

Originality/value
To the best of the authors’ knowledge, previous literature has not tested or confirmed the effects of PI related to two groups of robotic service delivery tasks on utilitarian variables. This study contributes to the literature by examining how different robotic service delivery tasks are linked to the TAM framework in a hotel setting.
Performance evaluation of acrylate terpolymer based coating on anti-carbonation
Authors: Nashed Youssef L. , Zahran Fouad , Youssef Mohamed Adel , Mohamed Manal G. , Mazrouaa Azza M. 
Published: November 2022

Purpose
The purpose of this study is to examine how well reinforced concrete structures can be shielded against concrete carbonation using anti-carbonation coatings based on synthetic polymer.

Design/methodology/approach
Applying free radical polymerization, an acrylate terpolymer emulsion that a surfactant had stabilized was created. A thermogravimetric analysis, minimum film-forming temperature, Fourier transform infrared spectroscopy and particle size distribution are used to characterize the prepared eco-friendly water base acrylate terpolymer emulsion. Using three different percentages of the acrylate terpolymer emulsion produced, 35%, 45% and 55%, the anti-carbonation coating was formed. Tensile strength, tensile strain, elongation, crack-bridging ability, carbon dioxide permeability, chloride ion diffusion, average pull-off adhesion strength, water vapor transmission, gloss, wet scrub resistance, QUV/weathering and storage stability are the characteristics of the anti-carbonation coating.

Findings
The formulated acrylate terpolymer emulsion enhances anti-carbonation coating performance in CO2 permeability, Cl-diffusion, crack bridging, pull-off adhesion strength and water vapor transmission. The formed coating based on the formulated acrylate terpolymer emulsion performed better than its commercial counterpart.

Practical implications
To protect the steel embedded in concrete from corrosion and increase the life span of concrete, the surface of cement is treated with an anti-carbonation coating based on synthetic acrylate terpolymer emulsion.

Social implications
In addition to saving lives from building collapse, it maintains the infrastructure for the long run.

Originality/value
The anti-carbonation coating, which is based on the synthetic acrylate terpolymer emulsion, is environmentally benign and stops the entry of carbon dioxide and chlorides, which are the main causes of steel corrosion in concrete.