bluuebunny/crossref_metadata_2025_split huggingface dataset:
An archetypes approach to malaria intervention impact mapping: a new framework and example application
Authors: Bertozzi-Villa Amelia , Bever Caitlin , Gerardin Jaline , Proctor Joshua L. , Wu Meikang , Harding Dennis , Hollingsworth T. Deirdre , Bhatt Samir , Gething Peter W. 
Published: August 2022

AbstractBackgroundAs both mechanistic and geospatial malaria modeling methods become more integrated into malaria policy decisions, there is increasing demand for strategies that combine these two methods. This paper introduces a novel archetypes-based methodology for generating high-resolution intervention impact maps based on mechanistic model simulations. An example configuration of the framework is described and explored.MethodsFirst, dimensionality reduction and clustering techniques were applied to rasterized geospatial environmental and mosquito covariates to find archetypal malaria transmission patterns. Next, mechanistic models were run on a representative site from each archetype to assess intervention impact. Finally, these mechanistic results were reprojected onto each pixel to generate full maps of intervention impact. The example configuration used ERA5 and Malaria Atlas Project covariates, singular value decomposition, k-means clustering, and the Institute for Disease Modeling’s EMOD model to explore a range of three-year malaria interventions primarily focused on vector control and case management.ResultsRainfall, temperature, and mosquito abundance layers were clustered into ten transmission archetypes with distinct properties. Example intervention impact curves and maps highlighted archetype-specific variation in efficacy of vector control interventions. A sensitivity analysis showed that the procedure for selecting representative sites to simulate worked well in all but one archetype.ConclusionThis paper introduces a novel methodology which combines the richness of spatiotemporal mapping with the rigor of mechanistic modeling to create a multi-purpose infrastructure for answering a broad range of important questions in the malaria policy space. It is flexible and adaptable to a range of input covariates, mechanistic models, and mapping strategies and can be adapted to the modelers’ setting of choice.
The late ISC pathway interactome reveals mitosomal-cytoplasmic crosstalk in Giardia intestinalis
Authors: Motyčková Alžběta , Voleman Luboš , Najdrová Vladimíra , Marková Lenka , Benda Martin , Dohnálek Vít , Janowicz Natalia , Malych Ronald , Šuťák Róbert , Ettema Thijs J. G. , Svärd Staffan , Stairs Courtney W. , Doležal Pavel 
Published: August 2022

ABSTRACTMitochondrial metabolism is entirely dependent on the biosynthesis of the [4Fe-4S] clusters, which are part of the subunits of the respiratory chain. The mitochondrial late ISC pathway mediates the formation of these clusters from simpler [2Fe-2S] molecules and transfers them to client proteins. Here, we characterized the late ISC pathway in one of the simplest mitochondria, mitosomes, of the anaerobic protist Giardia intestinalis that lost the respiratory chain and other hallmarks of mitochondria. Identification of the late ISC interactome revealed unexpected involvement of the aerobic marker protein BolA and specific interaction of IscA with the outer mitosomal membrane. Although we confirmed that the synthesis of the Fe-S cluster remained the only metabolic role of mitosomes, we also showed that mitosomes lack client proteins that require the [4Fe-4S] cluster. Instead, by knocking out the bolA gene from the G. intestinalis genome, we showed that, unlike aerobic mitochondria, the late ISC mitosomal pathway is involved in the assembly of cytosolic [4Fe-4S] clusters. Thus, this work reveals an unexpected link between the formation of mitochondrial and cytosolic [4Fe- 4S] clusters. This may either be a consequence of mitochondrial adaptation to life without oxygen, or it represents a general metabolic coupling that has not been previously observed in the complex mitochondrial metabolism of aerobes.
Processing of Different Social Scales in the Human Brain
Authors: Roseman Moshe , Dunbar Robin I. M. , Arzy Shahar 
Published: August 2022

AbstractFor an individual to lead a healthy and fulfilling social life, it is essential to have relationships with multiple people who are at different levels of emotional closeness. Based on ethological, sociological and psychological evidence, social networks have been divided into five scales of emotional closeness, gradually increasing in size and decreasing in emotional proximity. Is this division also reflected in different brain processes? During functional MRI, participants compared their emotional closeness to different members of their social network. We examined the brain area that was differentially activated for levels of emotional closeness, and found that its vast majority (78%) showed preference for people who are closest to participants, including the temporoparietal junction, middle temporal gyrus, precuneus and dorsomedial prefrontal cortex. A different system, which includes the medial temporal lobe, retrosplenial cortex and ventromedial prefrontal cortex showed preference for all other social scales. Moreover, we found a significant correlation between brain responses to emotionally close people and smaller spaces (room, building) as well as between emotionally distant people and larger spaces (neighborhood, city). Finally, brain activity at the default mode network (DMN) was associated with social scale preference, such that its subnetwork DMN A, related to social processing, showed preference to closer social scales, while DMN C, related to spatiotemporal processing, showed preference to farther social scales. Our results show that the cognitive processing of a few intimately close people differs from the rest of the social network, emphasizing their crucial role in social life.SignificanceWe divide the people in our lives according to levels of emotional closeness, called social scales, ranging from the few people who are the closest to us, in which we invest most of our social efforts and time (support clique), to the farthest level of ∼150 acquaintances. Here, we used neuroimaging to investigate the brain processing of different social scales. We found that the area of cortex dedicated to the support clique is much larger than that of all other scales and encompasses different brain regions. Interestingly, this division is similar to the one between processing of small and larger spaces, and processed by different subregions of the default mode network. Our study emphasizes the importance of close relationships in our social lives as found in the brain.
Universal mechanism of hormone and allosteric agonist mediated activation of glycoprotein hormone receptors as revealed by structures of follicle stimulating hormone receptor
Authors: Duan Jia , Xu Peiyu , Zhang Huibing , Luan Xiaodong , Yang Jiaqi , Mao Chunyou , Shen Dan-Dan , Ji Yujie , He Xinheng , Cheng Xi , Jiang Hualiang , Jiang Yi , Zhang Shuyang , Zhang Yan , Xu H. Eric 
Published: August 2022

AbstractFollicle stimulating hormone (FSH) is an essential glycoprotein hormone for human reproduction, which functions are mediated by a G protein-coupled receptor, FSHR. Aberrant FSH-FSHR signaling causes infertility and ovarian hyperstimulation syndrome. Here we report cryo-EM structures of FSHR in both inactive and active states, with the active structure bound to FSH and an allosteric agonist compound 21f. The structures of FSHR are similar to other glycoprotein hormone receptors, highlighting a conserved activation mechanism of hormone-induced receptor activation. Compound 21f formed extensive interactions with the TMD to directly activate FSHR. Importantly, the unique residue H6157.42 in FSHR plays an essential role in determining FSHR selectivity for various allosteric agonists. Together, our structures provide a molecular basis of FSH and small allosteric agonist-mediated FSHR activation, which could inspire the design of FSHR-targeted drugs for the treatment of infertility and controlled ovarian stimulation for in vitro fertilization.
High-throughput profiling of sequence recognition by tyrosine kinases and SH2 domains using bacterial peptide display
Authors: Li Allyson , Voleti Rashmi , Lee Minhee , Gagoski Dejan , Shah Neel H. 
Published: August 2022

AbstractTyrosine kinases and SH2 (phosphotyrosine recognition) domains have binding specificities that depend on the amino acid sequence surrounding the target (phospho)tyrosine residue. Although the preferred recognition motifs of many kinases and SH2 domains are known, we lack a quantitative description of sequence specificity that could guide predictions about signaling pathways or be used to design sequences for biomedical applications. Here, we present a platform that combines genetically-encoded peptide libraries and deep sequencing to profile sequence recognition by tyrosine kinases and SH2 domains. We screened several tyrosine kinases against a million-peptide random library and used the resulting profiles to design high-activity sequences. We also screened several kinases against a library containing thousands of human proteome-derived peptides and their naturally-occurring variants. These screens recapitulated independently measured phosphorylation rates and revealed hundreds of phosphosite-proximal mutations that impact phosphosite recognition by tyrosine kinases. We extended this platform to the analysis of SH2 domains and showed that screens could predict relative binding affinities. Finally, we expanded our method to assess the impact of non-canonical and post-translationally modified amino acids on sequence recognition. This specificity profiling platform will shed new light on phosphotyrosine signaling and could readily be adapted to other protein modification/recognition domains.
PRMT5-mediated regulatory arginine methylation of RIPK3
Authors: Chauhan Chanchal , Del Val Ana Martinez , Niedenthal Rainer , Olsen Jesper Velgaard , Kotlyarov Alexey , Bekker-Jensen Simon , Gaestel Matthias , Menon Manoj B. 
Published: August 2022

AbstractThe TNF receptor-interacting protein kinases (RIPK)-1 and 3 are regulators of extrinsic cell death response pathways, where RIPK1 makes the cell-survival or death decisions by associating with distinct complexes mediating survival signaling, caspase activation or RIPK3-dependent necroptotic cell death in a context dependent manner. Using a mass spectrometry-based screen to find new components of the ripoptosome/necrosome, we discovered the protein-arginine methyltransferase (PRMT)-5 as a direct interaction partner of RIPK1. Interestingly, RIPK3 but not RIPK1 was then found a target of PRMT5-mediated symmetric arginine dimethylation. A conserved arginine residue in RIPK3 (R486 in human, R415 in mouse) was identified as the evolutionarily conserved target for PRMT5-mediated symmetric dimethylation and the mutations R486A and R486K in human RIPK3 almost completely abrogated its methylation. Rescue experiments using these non-methylatable mutants of RIPK3 demonstrated PRMT5-mediated RIPK3 methylation to act as an efficient mechanism of RIPK3-mediated feedback control on RIPK1 activity and function. Therefore, this study reveals PRMT5-mediated RIPK3 methylation as a novel modulator of RIPK1-dependent signaling.
Shock drives a highly coordinated transcriptional and DNA methylation response in the endothelium
Authors: Ramos Ramon Bossardi , Martino Nina , Chuy Dareen , Lu Shuhan , Balasubramanian Uma , Di John Portela Iria , Vincent Peter A. , Adam Alejandro P. 
Published: August 2022

AbstractEndothelial dysfunction is a critical factor in promoting organ failure during septic shock. Organ dysfunction during shock increases the risk of long-term sequelae in survivors through mechanisms that remain unknown. We postulated that vascular dysfunction during shock contributes to the long-term morbidity post shock through transcriptional and epigenetic changes within the endothelium. As we have previously demonstrated that IL-6/JAK/STAT3 signaling in endothelial cells contributes to the inflammatory response following endotoxin, we performed cross-omics analyses on kidney endothelium from acute endotoxin-challenged mice lacking or not the JAK/STAT3 inhibitor SOCS3. This analysis revealed significant DNA methylation changes upon proinflammatory signaling that was significantly associated with transcriptional activity through AP1, STAT, and IRF families, suggesting a mechanism driving transcription-induced gene-specific methylation changes. In vitro, we demonstrated that IL-6 induces similar changes in DNA methylation. Specific genes showed DNA methylation changes in response to an IL-6+R challenge, and consistently, changes in their expression levels by 72 hours of IL-6+R treatment. Further, changes in the endothelial methylome remain in place for prolonged periods in absence of IL-6, suggesting that this cytokine may elicit transcriptional changes long after the resolution of inflammation. Also, demonstrated that DNA methylation changes could directly alter the expression of these genes and that STAT3 activation had a causal role in this transcriptional response. Our findings provide evidence for a critical role for IL-6 signaling in regulating shock-induced epigenetic changes and sustained endothelial activation, offering a new therapeutic target to limit vascular dysfunction and prevent long-term organ damage.Abstract Figure
Serological surveillance for wild rodent infection with SARS-CoV-2 in Europe
Authors: Bourret Vincent , Dutra Lara , Alburkat Hussein , Mäki Sanna , Lintunen Ella , Wasniewski Marine , Kant Ravi , Grzybek Maciej , Venkat Vinaya , Asad Hayder , Pradel Julien , Bouilloud Marie , Leirs Herwig , Colombo Valeria Carolina , Sluydts Vincent , Stuart Peter , McManus Andrew , Eccard Jana A. , Firozpoor Jasmin , Imholt Christian , Nowicka Joanna , Goll Aleksander , Ranc Nathan , Castel Guillaume , Charbonnel Nathalie , Sironen Tarja 
Published: August 2022

AbstractWe report serological surveillance for exposure to SARS-CoV-2 in 1,237 wild rodents and other small mammals across Europe. All samples were negative with the possible exception of one. Given the ongoing circulation of this virus in humans and potential host jumps, we suggest such surveillance be continued.
The effect of capital structure, operating efficiency and non-interest income on bank profitability: new evidence from Asia
Authors: Mehzabin Saima , Shahriar Ahanaf , Hoque Muhammad Nazmul , Wanke Peter , Azad Md. Abul Kalam 
Published: July 2022

PurposeThe Asian banking system has been appreciated with many distinct qualities including consistent in profitability. Many studies have examined the profitability of Asian banking sector from diverse perspectives. However, studies on bank profitability in connection to the capital structure, operating efficiency and non-interest income are only a few. This study investigates the influence of capital structure as estimated by leverage ratio and long-term debt, operating efficiency and non-interest income on the profitability of the banking industry in 28 countries of Asia.Design/methodology/approachThis paper utilizes fixed effect regression model by involving panel data with sample of 492 banks from 28 countries of Asia for the time span of 15 years from 2004 to 2018.FindingsThe results confirm that an increase in total debt ratio increases the profit margin of the bank as supported by the agency cost theory, suggesting that the debt financing increases the profitability of the firm. In addition, the findings reveal that lowering the operating expenses and managing of costs effectively can boost the profitability of bank. Furthermore, non-interest income plays a vital role when the interest rates are lower. Hence the study suggests that a careful investment in this sector can generate income as well as increase the profit margin of the banking arena.Originality/valueThe paper examines the profitability of bank by including impact of leverage ratio and long-term debt as a measure of capital structure along with the influence of operational efficiency and non-interest income which contributes to the understanding of the existing literature.
The antecedents and outcomes of career optimism: a meta-analysis
Authors: Lin Xinqi , Luan Yuxiang , Zhao Kai , Zhao Teng , Zhao Guolong 
Published: July 2022

PurposeGiven its importance, career optimism (CO) has drawn much attention from researchers. Fruitful evidence has been accumulated; unfortunately, a quantitative review is still lacking, which would limit the continuous development of this field. To address this, this paper uses the meta-analysis technology to evaluate the links between CO and its antecedents and outcomes.Design/methodology/approachThis study used Hunter–Schmidt method random effect meta-analysis technology to systematically evaluate the true score correlations between CO and its antecedents and outcomes.FindingsAmong the CO antecedents, this study found significant links between CO and agreeableness (ρ = 0.11), career adaptability (ρ = 0.55), career knowledge (ρ = 0.43), career decision self-efficacy (ρ = 0.52), social support (ρ = 0.30), conscientiousness (ρ = 0.54), extraversion (ρ = 0.38), gender (ρ = 0.07), GPA (ρ = 0.11), neuroticism (ρ = −0.42), and openness (ρ = 0.27). Moreover, among the CO outcomes, significant links have been found between CO and academic satisfaction (ρ = 0.43), career choice satisfaction (ρ = 0.44), career decisiveness (ρ = 0.37), depersonalization (ρ = −0.48), and emotional exhaustion (ρ = −0.59).Originality/valueBy conducting the first meta-analysis of CO, our study contributes to the CO literature. Additionally, our study increases the knowledge of CO, which would help leaders in the school or workplace to understand the significance of CO better and thereby take actions to intervene and increase students or employees' CO.
Strategic collaboration in agro-industrial clusters: territorial dynamics within the dairy industry in Uruguay
Authors: Galaso Pablo , Rodríguez Miranda Adrián 
Published: August 2022

PurposeInquiring about the patterns of interaction within clusters can provide a valuable insight into the cooperation and competition strategies followed by firms. However, such internal patterns are difficult to identify using conventional methods. This study aims to apply a social network analysis approach to identify and analyze different sub-groups of firms within a dairy cluster. These sub-groups seem to respond to different forms of productive organization, with different levels of territorial anchorage.Design/methodology/approachThe authors study the dairy cluster in the south-west of Uruguay, where one of the country’s main industries is located. The authors use data from semi-structured interviews applied to managing directors of 40 dairy industrial firms. The authors analyze the collaboration network among firms and industry support organizations. Using a community detection algorithm, the authors identify strategic groups of firms and organizations within the network. The authors analyze information from the interviews to delve deeper into the strategies pursued by actors in each of these sub-groups.FindingsThe four groups identified by the algorithm respond to particular logics associated not only with collaborative behavior, but also with territorial distribution and competitive strategies pursued by firms. In particular, these communities show a positive association between the centrality of their nodes in the network, the size of their firms, their export orientation and their innovative capacity. These associations indicate the co-existence, within the cluster, of different local productive systems and other forms of productive organization.Originality/valueThe paper illustrates how different strategies of firms within a cluster can be understood using social network analysis. This approach is particularly interesting in agri-food clusters, where their wider dispersion in the territory often implies their firms following different collaborative and competitive strategies, and different levels of territorial anchorage.
Optimal fiscal policy in a model with reciprocity in labor relations: the case of Bulgaria
Authors: Vasilev Aleksandar 
Published: August 2022

PurposeThis paper explores the effects of fiscal policy in an economy with reciprocity in labor relations and fair wages, consumption taxes and a common income tax rate in place.Design/methodology/approachTo this end, a dynamic general-equilibrium model with government sector is calibrated to Bulgarian data (1999–2018). Two regimes are compared and contrasted – the exogenous (observed) vs optimal policy (Ramsey) case. The focus of the paper is on the relative importance of consumption vs income taxation, as well as on the provision of utility-enhancing public services. Bulgarian economy was chosen as a case study due to its major dependence on consumption taxation as a source of tax revenue.Findings(1) The optimal steady-state income tax rate is zero; (2) the benevolent Ramsey planner provides the optimal amount of the utility-enhancing public services, which are now three times lower; (3) the optimal steady-state consumption tax needed to finance the optimal level of government spending is 18:7%.Originality/valueThis is the first study on optimal fiscal policy with reciprocity in labor relations.
Robotic process automation adoption: contextual factors from service sectors in an emerging economy
Authors: Sharma Chitra , Bharadwaj Sangeeta Shah , Gupta Narain , Jain Hemant 
Published: August 2022

PurposeThe study aimed to examine the robotic process automation (RPA) contextual (center of excellence and scalability) and the multidisciplinary (TOE) determinants of RPA adoption in service industries in the emerging economy.Design/methodology/approachTen factors were identified through literature surveys and popular studies grounded in technology, organization and environment. SPSS AMOS SEM is used for scale measurement and hypotheses testing. A sample of 313 respondents was collected from middle to above middle management executives of service industries from India. The authors tested the hidden layers and non-linear relationships using artificial neural network (ANN) analysis.FindingsThe low complexity, center of excellence (CoE), and industry/business partner pressure were significant to the RPA adoption in service industries in emerging economies. Counterintuitively, the scalability showed a negative influence on the RPA adoption, and the process capability did not show influence. The results of SEM and ANN were consistent.Research limitations/implicationsThis research can unfold the RPA adoption scholarly debate to multiple services industries beyond the telecom sector in emerging economies.Practical implicationsRPA is a disruptive technology on the artificial intelligence (AI) continuum. It has the potential to change the ways of working and enable technology-driven transformation. However, despite having thriving service industries that can benefit from RPA, emerging economies lag in adoption compared to the developed nations.Social implicationsThe RPA and automation can bring transformation to human society. Large economies such as India and China have large-scale demand for services, and the waiting lines are a common issue struggled by society. RPA can address the scalability issues of several services.Originality/valueThis study is among the first to examine technology-organization-environment (TOE) with RPA, including RPA contextual variables such as the CoE and scalability. Literature reports TOE applications on several emerging technologies of Industry 4.0 such as cloud, blockchain, big data and 3 Dimensional Printing (3DP), but no or little reported studies around RPA in services industries in emerging markets.