bluuebunny/crossref_metadata_2025_split huggingface dataset:
To design or not to design? Comparison of beetle ultraconserved element probe set utility based on phylogenetic distance, breadth, and method of probe design
Authors: Gustafson Grey T. , Glynn Rachel D. , Short Andrew E. Z. , Tarasov Sergei , Gunter Nicole L. 
Published: January 2023

AbstractTailoring ultraconserved element (UCE) probe set design to focal taxa has been demonstrated to improve locus recovery and phylogenomic inference. However, beyond conducting expensivein vitrotesting, it remains unclear how best to determine whether an existing UCE probe set is likely to suffice for phylogenomic inference, or if tailored probe design will be desirable. Here we investigate the utility of eight different UCE probe sets for thein silicophylogenomic inference of scarabaeoid beetles. Probe sets tested differed in terms of (1) how phylogenetically distant from Scarabaeoidea taxa those used during probe design are, (2) breadth of phylogenetic inference probe set was designed for, and (3) method of probe design. As part of this study, two new UCE probe sets are produced for the beetle family Scarabaeidae and superfamily Hydrophiloidea. We find that, predictably, probe set utility decreases with increasing phylogenetic distance of design taxa from focal taxa, as well as with narrower breadth of phylogenetic inference probes were designed for. We also confirm previous findings regarding ways to optimize UCE probe design. Finally, we make suggestions regarding assessment of need forde novoprobe design and reinforce previous proposed methods for maximizing UCE probe design to improve phylogenomic inference.
Targeting the deNEDDylating enzyme NEDP1 to ameliorate ALS phenotypes through Stress Granules dissolution
Authors: Kassouf Toufic , Shrivastava Rohit , Meszka Igor , Bailly Aymeric , Polanowska Jolanta , Trauchessec Helene , Mandrioli Jessica , Carra Serena , Xirodimas Dimitris P. 
Published: January 2023

SummaryIn Amyotrophic Lateral Sclerosis (ALS) motor neuron disease, mutations in proteins that upon stress localize within cytoplasmic protein inclusions called Stress Granules (SGs), are linked to the formation of aberrant inclusions, which are related to neuronal cell death. By combining studies in human cells andC. elegansincluding the use of Nanobodies, we found that inhibition of NEDP1, the enzyme responsible for the processing and deconjugation of the Ubiquitin-like molecule NEDD8 from substrates, promotes the elimination both of physiological and pathological SGs. The hyper-NEDDylation of Poly-(ADP-ribose) polymerase-1 enzyme upon NEDP1 inhibition compromises PAR production and is a key mechanism for the observed SG phenotype. Importantly, the above-described effects are related to improved cell survival in human cells, and inC. elegans, NEDP1 deletion ameliorates ALS-phenotypes related to animal motility. Our studies reveal NEDP1 as potential therapeutic target for ALS, based on the elimination of aberrant SGs.
Thyroid hormone-dependent apoptosis during metamorphosis inCiona robustainvolves both bilaterian-ancestral and vertebrate-derived processes
Authors: Nelly Godefroy , Emilie Le Goff , Qiaowei Pan , Stephen Baghdiguian , Mélanie Debiais-Thibaud , Camille Martinand-Mari 
Published: January 2023

ABSTRACTChordate metamorphosis is a postembryonic larva-to-juvenile transition triggered by thyroid hormones and their specific receptors (TR). This crucial developmental event shows a wide morphological diversity among different chordate lineages and is characterized by ecological, morphological, metabolic and behavioral changes that can be drastic. One of the most studied models is the amphibian Xenopus, whose tadpole metamorphosis includes apoptosis-induced tail regression dependent on the thyroid hormone pathway. In an evolutionary context, we used the ascidian model, the extant closest group to vertebrates, in which the swimming larva transforms to a sessile filter-feeding juvenile during metamorphosis, to study the role of thyroid hormones in this transformation. The ascidian metamorphosis is also characterized by an apoptosis-driven tail regression as in Xenopus. However, whether this apoptosis-driven process is dependent on the thyroid hormone has not yet been elucidated.In this study, we interfered with thyroid hormone signaling during tail regression of the ascidianCiona robustato investigate whether (i) thyroid hormone is involved in the regulation of developmental apoptosis, and (ii) apoptosis leading to tail regression involves its classical molecular pathways. We described specific gene expression landmarks as well as apoptosis dynamics during larva metamorphosis under thyroid hormone exposure and thyroid hormone inhibition treatments. We provide evidence thatCiona robustametamorphosis involves thyroid hormone-dependent apoptosis, similar to other studied chordates. However, the mode of action of thyroid hormone shows great variation compared to the classically described scheme in chordates, both in thyroid hormone/TR interactions and in the apoptotic pathway.
CoVAMPnet: Comparative Markov State Analysis for Studying Effects of Drug Candidates on Disordered Biomolecules
Authors: Marques Sérgio M. , Kouba Petr , Legrand Anthony , Sedlar Jiri , Disson Lucas , Planas-Iglesias Joan , Sanusi Zainab , Kunka Antonin , Damborsky Jiri , Pajdla Tomas , Prokop Zbynek , Mazurenko Stanislav , Sivic Josef , Bednar David 
Published: January 2023

ABSTRACTComputational study of the effect of drug candidates on intrinsically disordered biomolecules is challenging due to their vast and complex conformational space. Here we developed a Comparative Markov State Analysis (CoVAMPnet) framework to quantify changes in the conformational distribution and dynamics of a disordered biomolecule in the presence and absence of small organic drug candidate molecules. First, molecular dynamics trajectories are generated using enhanced sampling, in the presence and absence of small molecule drug candidates, and ensembles of soft Markov state models (MSMs) are learned for each system using unsupervised machine learning. Second, these ensembles of learned MSMs are aligned across different systems based on a solution to an optimal transport problem. Third, the directional importance of inter-residue distances for the assignment to different conformational states is assessed by a discriminative analysis of aggregated neural network gradients. This final step provides interpretability and biophysical context to the learned MSMs. We applied this novel computational framework to assess the effects of ongoing phase 3 therapeutics tramiprosate (TMP) and its metabolite 3-sulfopropanoic acid (SPA) on the disordered Aβ42 peptide involved in Alzheimer’s disease. Based on adaptive sampling molecular dynamics and CoVAMPnet analysis, we observed that both TMP and SPA preserved more structured conformations of Aβ42 by interacting non-specifically with charged residues. SPA impacted Aβ42 more than TMP, protecting α-helices and suppressing the formation of aggregation-prone β-strands. Experimental biophysical analyses showed only mild effects of TMP/SPA on Aβ42, and activity enhancement by the endogenous metabolization of TMP into SPA. Our data suggest that TMP/SPA may also target other biomolecules than Aβ peptides. The CoVAMPnet method is broadly applicable to study the effects of drug candidates on the conformational behavior of intrinsically disordered biomolecules.TOC Graphic
Customer experiences in the era of artificial intelligence (AI) in context to FinTech: a fuzzy AHP approach
Authors: Arora Anchal , Gupta Sanjay , Devi Chandrika , Walia Nidhi 
Published: January 2023

PurposeThe financial technology (FinTech) era has brought a revolutionary change in the financial sector’s customer experiences at the national and global levels. The importance of artificial intelligence (AI) in the context of FinTech services for enriching customer experiences has become a new norm in this modern era of technological advancement. So, it becomes crucial to understand the customer’s perspective. The current research ranks the factors and sub-factors influencing customers’ perceptions of AI-based FinTech services.Design/methodology/approachThe sample size for this study was decided to be 970 respondents from four Indian cities: Mumbai, Delhi, Kolkata and Chennai. The Fuzzy-AHP technique was used to identify the primary factors and sub-factors influencing customers’ experiences with AI-enabled finance services. The factors considered in the study were service quality, trust commitment, personalization, perceived convenience, relationship commitment, perceived sacrifice, subjective norms, perceived usefulness, attitude and vulnerability. The current research is both empirical and descriptive.FindingsThe study’s three top factors are service quality, perceived usefulness and perceived convenience, all of which have a significant impact on customers’ experience with AI-enabled FinTech services discussing sub-criteria three primary criteria for customers’ experience for FinTech services include: “Using FinTech would increase my effectiveness in managing a portfolio (A2)”, “My peer groups and friends have an impact on using FinTech services (SN3)” and “Using FinTech would increase my efficacy in administering portfolio (PU2)”.Research limitations/implicationsThe current study is limited to four Indian cities, with 10 factors to understand customers’ preferences in FinTech. Further research can focus on other dimensions like perceived ease of use, familiarity, etc. Future studies can have a broader view of different geographical locations and consider new tech to understand customer perceptions better.Practical implicationsThe study’s findings will significantly assist businesses in determining the primary aspects influencing customers’ experiences with AI-enabled financial services. As a result, they will develop strategies and policies to entice clients to use AI-powered FinTech services.Originality/valueExisting AI research investigated several vital topics in the context of FinTech services. On the other hand, the current study ranked the criteria in understanding customer experiences. The research will substantially assist marketers, business houses, academicians and practitioners in understanding essential facets influencing customer experience and contribute significantly to the literature.
Big data analytics capabilities and supply chain performance: testing a moderated mediation model using partial least squares approach
Authors: AL-Khatib Ayman Wael , Ramayah T. 
Published: January 2023

PurposeIn this study, the authors investigate the effect of big data analytics capability (BDAC) on supply chain performance (SCP) to assess the mediating effect of supply chain innovation (SCI) and the moderating effect of a data-driven culture (DDC).Design/methodology/approachThe authors collected the primary data through an online questionnaire survey from the manufacturing sector operating in Jordan. The authors used 420 samples for the final data analysis, which the authors performed via partial least squares structural equation modelling using SmartPLS 3.3.9 software.FindingsThe results indicate that BDAC has a strong relationship with SCI and SCP. SCI shows a positive relationship with SCP as well as a mediating effect on SCI. The authors confirmed that DDC moderated the relationship between SCI and SCP.Originality/valueThe authors developed a conceptual and empirical model to investigate the relationship between BDAC, SCI, DDC and SCP. The authors contributed new theoretical and managerial insights that add value to the supply chain management literature through testing the moderated-mediated model of these constructs in Jordan’s manufacturing sector.
The impact of brand origin and CSR actions on consumer perceptions in retail banking during a crisis
Authors: Tosun Petek , Köylüoğlu A. Selçuk 
Published: January 2023

PurposeConsumers’ corporate social responsibility (CSR) expectations have increased in the new coronavirus (COVID-19) pandemic, while many financial institutions have supported society with their health-related CSR actions. This study examines the impact of CSR actions and brand origin on consumer attitudes, CSR perceptions, customer-based brand equity (CBBE) and supportive communication intent in retail banking during the crisis from signaling and stakeholder theory perspectives.Design/methodology/approachA 2 (foreign vs. local brand) x 2 (COVID-19-related vs. another CSR action) between-subjects factorial design was used to analyze consumer data.FindingsCSR actions of local brands created more positive attitudes, CSR perceptions and greater CBBE and supportive communication intent than foreign banks. However, CSR action (COVID-19-related vs. another) did not significantly influence consumer attitudes, CSR perceptions, CBBE and supportive communication intent.Originality/valueThis research has shown the significant impact of brand origin on consumer perceptions in response to CSR actions during the pandemic. It has suggested an original conceptual framework and presented timely empirical findings for retail banking in the pandemic period, which can exemplify a crisis period shaped by uncertainty. Besides, it extended the previous literature by focusing on the interaction between brand origin and CSR actions in shaping consumers’ CSR and brand perceptions. It is among the first studies examining brand origin’s impact on supportive communication intent.
Financial performance of firms with supply chains during the COVID-19 pandemic: the roles of dynamic capability and supply chain resilience
Authors: Juan Shih-Jung , Li Eldon Y. 
Published: January 2023

PurposeThis study proposes an integrated model to explore the relationships between dynamic capability and supply chain resilience (SCRE) and the relationships' impacts on firms' financial performance with supply chains (FPwSC) during the coronavirus disease 2019 (COVID-19) pandemic.Design/methodology/approachBased on resource-based theory and knowledge-based theory, the dynamic capability is classified into resource-based dynamic capability (RBDC) and knowledge-based dynamic capability (KBDC). The study collects 158 useable survey samples from manufacturers in Taiwan and analyzes the samples with the structural equation model.FindingsThe results show that knowledge is power; KBDC is crucial for FPwSC, SCRE and RBDC. In addition, SCRE mediates the relationship between KBDC and FPwSC. Finally, RBDC significantly suppresses FPwSC.Research limitations/implicationsFuture researchers could replicate this study in other industries and expand this to other countries to generalize the results.Practical implicationsA firm with KBDC can adopt and implement strategies that exploit its internal strengths to respond to environmental opportunities, overcome internal weaknesses and mitigate external threats. Furthermore, a firm should fully utilize SCRE with proactive and reactive strategies. Exercising a firm's KBDC could facilitate SC collective intelligence to handle the risk of SC disruption and vice versa.Originality/valueThe study is the first to combine KBDC, RBDC and SCRE into an integrated model for FPwSC. Moreover, this study reveals that resilience relies on knowledge, not resources, as evidenced by SCRE being affected significantly by KBDC but not RBDC.
Developing SME performance management practices: interventions for improving productivity
Authors: Jones Oliver William , Devins David , Barnes Greg 
Published: January 2023

PurposeThe paper is a proof of concept (PoC) intervention study aimed for developing performance management (PM) practices in manufacturing small and medium-sized enterprises (SMEs) with the longer-term aim enabling the SMEs to improve their productivity. The intervention was designed and deployed by a collaborative quartet of academics, management consultants, accountancy firm and a commercial bank manager.Design/methodology/approachThe paper firstly musters a set of initialising PM practices aligned to productivity improvement. These are utilised to design a knowledge transfer intervention for deployment with a set of manufacturing SMEs incorporating some associated productivity tools. The evaluation of the intervention utilised a case study approach founded on a logic model of the intervention to assess the development of the PM practices.FindingsThe intervention contributed to a partial development of the mustered practices and the productivity diagnostic based on the multi-factor productivity (MFP) abstraction and a data extraction protocol had the strongest impact. The study revealed the importance of the three interlaced factors: Depth of engagement, feedback opportunities and the intervention gradient (the increase of independent action from the participating SME's and the diminishment of the external intervention effort).Research limitations/implicationsThe case study is based on a limited number of individual SME's, and within just the manufacturing sector.Practical implicationsSME businesses will require a more sustained programme of interventions than this pilot to develop PM capability, and depth of engagement within the SME is critical. Professional stakeholders can be utilised in recruitment of firms for intervention programmes. Business can start developing PM capability prior to PMS implementation using the tools from this programme.Originality/valueThe productivity diagnostic tool, based on a synthesis of MFP and the performance pyramid, an array of potential initialising practices for PM capability and discovery of potential mechanisms for PM practice development.
Do executive remuneration decision-makers know what's going on? The gap between independence and institutional contexts
Authors: Perkins Stephen J. , Shortland Susan 
Published: January 2023

PurposeDrawing on institutional theory, this study aims to analyse the regulation of executive remuneration as espoused in the United Kingdom (UK) codified corporate governance principles, focussing on sources of advice to decision-makers, the nature of the advice sought and given, and interaction of those involved in the process.Design/methodology/approachA qualitative research design was used. Data were assembled from interviewing non-executive board/remuneration committee members; institutional investors; external remuneration consultants and internal human resources (HR)/reward specialists. Results were analysed in accordance with the Gioia technique.FindingsTensions inherent in the interpretation of corporate governance codes are illustrated. Emphasis on independent advice combined with constraints on decision-makers' capacity to navigate the nuances of a complex field and reputational concerns risks standardised instead of bespoke remuneration approaches aligned with corporate contexts.Practical implicationsThere is a role for internal HR advisors to add value through their potential to reduce the gap within remuneration committees between institutional contexts and independent decision-making, facilitating more strategic human resource management inspired executive remuneration.Originality/valueApplication of institutional theory indicates the relevance of balancing external with internal sources to secure advice that is horizontally and vertically aligned within an organisation to meet the letter and spirit of corporate governance norms. Extending the explanatory power of institutional theory, care is needed though not to overlook the normative underpinnings of professional advisors' own value sets.
Boosting propagule transport models with individual‐specific data from mobile apps
Authors: Fischer Samuel M. , Ramazi Pouria , Simmons Sean , Poesch Mark S. , Lewis Mark A. 
Published: January 2023

Abstract

Management of invasive species and pathogens requires information about the traffic of potential vectors. Such information is often taken from vector traffic models fitted to survey data. Here, user‐specific data collected via mobile apps offer new opportunities to obtain more accurate estimates and to analyse how vectors' individual preferences affect propagule flows. However, data voluntarily reported via apps may lack some trip records, adding a significant layer of uncertainty. We show how the benefits of app‐based data can be exploited despite this drawback.

Based on data collected via an angler app, we built a stochastic model for angler traffic in the Canadian province Alberta. There, anglers facilitate the spread of whirling disease, a parasite‐induced fish disease. The model is temporally and spatially explicit and accounts for individual preferences and repeating behaviour of anglers, helping to address the problem of missing trip records.

We obtained estimates of angler traffic between all subbasins in Alberta. The model's accuracy exceeds that of direct empirical estimates even when fewer data were used to fit the model. The results indicate that anglers' local preferences and their tendency to revisit previous destinations reduce the number of long interwaterbody trips potentially dispersing whirling disease. According to our model, anglers revisit their previous destination in 64% of their trips, making these trips irrelevant for the spread of whirling disease. Furthermore, 54% of fishing trips end in individual‐specific spatially contained areas with mean radius of 54.7 km. Finally, although the fraction of trips that anglers report was unknown, we were able to estimate the total yearly number of fishing trips in Alberta, matching an independent empirical estimate.

Policy implications. We make two major contributions: (1) we provide a model that uses mobile app data to boost the mechanistic accuracy of classic propagule transport models, and (2) we demonstrate the importance of individual‐specific behaviour of vectors for propagule transport. Ignoring vectors' local preferences and their tendency to revisit previous destinations can lead to significant overestimates of vector traffic and biased estimates of propagule flows. This has clear implications for the management of invasive species and animal diseases.