bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overexpression of PSR1 inChlamydomonas reinhardtiiinduces luxury phosphorus uptake
Authors: Slocombe Stephen P. , Zúñiga-Burgos Tatiana , Chu Lili , Mehrshahi Payam , Davey Matthew P. , Smith Alison G. , Camargo-Valero Miller Alonso , Baker Alison 
Published: November 2022

AbstractRemediation using micro-algae offers an attractive solution to environmental phosphate (Pi) pollution. However, for maximum efficiency, pre-conditioning of algae to induce ‘luxury phosphorus (P) uptake’ is needed. Here we show that natural pre-conditioning can be mimicked through over-expression of a single gene, the global regulator PSR1 (Myb transcription factor: Phosphate Starvation Response 1), raising P levels to 8% dry cell weight from 2% in control. Complete removal of Pioccurred in log phase, unlike the control. This was associated with increases in PolyP granule size and uptake of Mg2+, the principal counterion. Hyper-accumulation of P depended on a feed-forward mechanism, where a small set of ‘Class I’ genes were activated despite abundant external Pilevels. This drove a reduction in external Pilevels, permitting more genes to be expressed (Class II), leading to more Pi-uptake. These discoveries enable a bio-circular approach of recycling nutrients from wastewater back to agriculture.TeaserManipulating a single gene drove uptake of P and a Mg2+counter-ion for increased PolyP accumulation.
Anticipatory and evoked visual cortical dynamics of voluntary temporal attention
Authors: Denison Rachel N. , Tian Karen J. , Heeger David J. , Carrasco Marisa 
Published: November 2022

AbstractWe can often anticipate the precise moment when a stimulus will be relevant for our behavioral goals. Voluntary temporal attention, the prioritization of sensory information at task-relevant time points, enhances visual perception. However, the neural mechanisms of voluntary temporal attention have not been isolated from those of temporal expectation, which reflects timing predictability rather than relevance. Here we used time-resolved steady-state visual evoked responses (SSVER) to investigate how temporal attention dynamically modulates visual activity when temporal expectation is controlled. We recorded MEG while observers directed temporal attention to one of two sequential grating targets with predictable timing. Meanwhile, we used a co-localized SSVER probe to continuously track visual cortical modulations both before and after the target stimuli. In the pre-target period, the SSVER gradually ramped up as the targets approached, reflecting temporal expectation. Furthermore, we found a low-frequency modulation of the SSVER, which shifted approximately half a cycle in phase according to which target was attended. In the post-target period, temporal attention to the first target transiently modulated the SSVER shortly after target onset. Thus, temporal attention dynamically modulates visual cortical responses via both periodic pre-target and transient post-target mechanisms to prioritize sensory information at precise moments.
Predicting environmental stressor levels with machine learning: a comparison between amplicon sequencing, metagenomics, and total RNA sequencing based on taxonomically assigned data
Authors: Hempel Christopher A. , Buchner Dominik , Mack Leoni , Brasseur Marie V. , Tulpan Dan , Leese Florian , Steinke Dirk 
Published: November 2022

AbstractBackgroundMicrobes are increasingly (re)considered for environmental assessments because they are powerful indicators for the health of ecosystems. The complexity of microbial communities necessitates powerful novel tools to derive conclusions for environmental decision-makers, and machine learning is a promising option in that context. While amplicon sequencing is typically applied to assess microbial communities, metagenomics and total RNA sequencing (herein summarized as omics-based methods) can provide a more holistic picture of microbial biodiversity at sufficient sequencing depths. Despite this advantage, amplicon sequencing and omics-based methods have not yet been compared for taxonomy-based environmental assessments with machine learning. In this study, we applied 16S and ITS-2 sequencing, metagenomics, and total RNA sequencing to samples from a stream mesocosm experiment that investigated the impacts of two aquatic stressors, insecticide and increased fine sediment deposition, on stream biodiversity. We processed the data using similarity clustering and denoising (only applicable to amplicon sequencing) as well as multiple taxonomic levels, data types, feature selection, and machine learning algorithms and evaluated the stressor prediction performance of each generated model for a total of 1,536 evaluated combinations of taxonomic datasets and data-processing methods.ResultsSequencing and data-processing methods had a substantial impact on stressor prediction. While omics-based methods detected much more taxa than amplicon sequencing, 16S sequencing outperformed all other sequencing methods in terms of stressor prediction based on the Matthews Correlation Coefficient. However, even the highest observed performance for 16S sequencing was still only moderate. Omics-based methods performed poorly overall, but this was likely due to insufficient sequencing depth. Data types had no impact on performance while feature selection significantly improved performance for omics-based methods but not for amplicon sequencing.ConclusionAmplicon sequencing might be a better candidate for machine-learning-based environmental stressor prediction than omics-based methods, but the latter require further research at higher sequencing depths to confirm this conclusion. More sampling could improve stressor prediction performance, and while this was not possible in the context of our study, thousands of sampling sites are monitored for routine environmental assessments, providing an ideal framework to further refine the approach for possible implementation in environmental diagnostics.
Robust identification of regulatory variants (eQTLs) using a differential expression framework developed for RNA-sequencing
Authors: Marrella Mackenzie A. , Biase Fernando H. 
Published: November 2022

AbstractBackgroundA gap currently exists between genetic variants and the underlying cell and tissue biology of a trait, and expression quantitative trait loci (eQTL) studies provide important information to help close that gap. However, two concerns that arise with eQTL analyses using RNA-sequencing data are normalization of data across samples and the data not following a normal distribution. Multiple pipelines have been suggested to address this. For instance, the most recent analysis of the human and farm Genotype-Tissue Expression (GTEx) project proposes using trimmed means of M-values (TMM) to normalize the data followed by an inverse normal transformation.ResultsIn this study, we reasoned that eQTL analysis could be carried out using the same framework used for differential gene expression (DGE), which uses a negative binomial model, a statistical test feasible for count data. Using the GTEx framework, we identified 38 significant eQTLs (P<5×10-8) following the ANOVA model and 15 significant eQTLs (P<5×10-8) following the additive model. Using a differential gene expression framework, we identified 2,471 and nine significant eQTLs (P<5×10-8) following an analytical framework equivalent to the ANOVA and additive model, respectively. When we compared the two approaches, there was no overlap of significant eQTLs between the two frameworks. Because we defined specific contrasts, we identified trans eQTLs that more closely resembled what we expect from genetic variants showing complete dominance between alleles. Yet, these were not identified by the GTEx framework.ConclusionsOur results show that transforming RNA-sequencing data to fit a normal distribution prior to eQTL analysis is not required when the DGE framework is employed, thus this may be more suitable for finding genes whose expression are impacted by genetic variants. Our approach detected biologically relevant variants that otherwise would not have been identified due to data transformation to fit a normal distribution.
In-silicodocking platform with serine protease inhibitor (SERPIN) structures identifies host cysteine protease targets with significance for SARS-CoV-2
Authors: Rodriguez Galvan Joaquín J , de Vries Maren , Belblidia Shiraz , Fisher Ashley , Prescott Rachel A , Crosse Keaton M , Mangel Walter F. , Duerr Ralf , Dittmann Meike 
Published: November 2022

ABSTRACTSerine Protease Inhibitors (SERPINs) regulate protease activity in various physiological processes such as inflammation, cancer metastasis, angiogenesis, and neurodegenerative diseases. However, their potential in combating viral infections, where proteases are also crucial, remains underexplored. This is due to our limited understanding of SERPIN expression during viral-induced inflammation and of the SERPINs’ full spectrum of target proteases. Here, we demonstrate widespread expression of human SERPINs in response to respiratory virus infections, bothin vitroandin vivo, alongside classical antiviral effectors. Through comprehensivein-silicodocking with full-length SERPIN and protease 3D structures, we confirm known inhibitors of specific proteases; more importantly, the results predict novel SERPIN-protease interactions. Experimentally, we validate the direct inhibition of key proteases essential for viral life cycles, including the SERPIN PAI-1’s capability to inhibit select cysteine proteases such as cathepsin L, and the serine protease TMPRSS2. Consequently, PAI-1 suppresses spike maturation and multi-cycle SARS-CoV-2 replication. Our findings challenge conventional notions of SERPIN selectivity, underscore the power ofin-silicodocking for SERPIN target discovery, and offer potential therapeutic interventions targeting host proteolytic pathways to combat viruses with urgent unmet therapeutic needs.SIGNIFICANCESerine protease inhibitors (SERPINs) play crucial roles in various physiological processes, including viral infections. However, our comprehension of the full array of proteases targeted by the SERPIN family has traditionally been limited, hindering a comprehensive understanding of their regulatory potential. We developed anin-silicodocking platform to identify new SERPIN target proteases expressed in the respiratory tract, a critical viral entry portal. The platform confirmed known and predicted new targets for every SERPIN examined, shedding light on previously unrecognized patterns in SERPIN selectivity. Notably, both key proteases for SARS-CoV-2 maturation were among the newly predicted targets, which we validated experimentally. This underscores the platform’s potential in uncovering targets with significance in viral infections, paving the way to define the full potential of the SERPIN family in infectious disease and beyond.
Streptomycesalleviate abiotic stress in plant by producing pteridic acids
Authors: Yang Zhijie , Strøbech Emil , Qiao Yijun , Konakall Naga Charan , Harris Pernille , Peschel Gundela , Agler-Rosenbaum Miriam , Weber Tilmann , Andreasson Erik , Ding Ling 
Published: November 2022

AbstractSoil microbiota can confer fitness advantages to plants and increase crop resilience to drought and other abiotic stressors. However, there is little evidence on the mechanisms correlating a microbial trait with plant abiotic stress tolerance. Here, we report thatStreptomyceseffectively alleviates the drought and salinity stress by producing spiroketal polyketide pteridic acid H (1) and its isomer F (2), both of which promote root growth inArabidopsisat a concentration of 1.3 nM under abiotic stress. Pteridic acids induce stress response genes expression in salinity-stressedArabidopsisseedlings. The bifunctional biosynthetic gene cluster of pteridic acids and antimicrobial elaiophylin is confirmed in vivo and mainly disseminated by vertical transmission which is geographically distributed in various environments. This discovery reveals a perspective for understanding plant-Streptomycesinteractions and provides a promising approach for utilising beneficialStreptomycesand their secondary metabolites in agriculture to mitigate the detrimental effects of climate change.
Beyond technology in smart cities: a multivocal literature review on data governance
Authors: Kvalvik Petter , Sánchez-Gordón Mary , Colomo-Palacios Ricardo 
Published: November 2022

PurposeSmart cities require data governance to articulate data sharing and use among relevant stakeholders. Given the lack of a comprehensive examination of this research topic, this study aims to review data governance publications to detect and categorize endeavors backing up data sharing in smart cities.Design/methodology/approachA systematic literature review was conducted, and 568 academic and professional sources were identified, but finally, only 10 relevant papers were selected.FindingsResults reveal that data governance must be based on well-defined mechanisms, procedures and roles to achieve accountability and responsibility in a multi-actor environment. Moreover, data governance should be adapted to address power imbalances among all interested parties.Research limitations/implicationsThe main limitation is the list of sources considered for the literature review. However, this study provides a holistic overview for researchers and professionals willing to know more about smart city data sharing.Originality/valueThis review identifies the data governance approaches supporting data sharing in smart cities, analyzes their data dimension, enhances the state-of-the-art literature on this topic and suggests possible areas for future research.
Modeling of planning function management in Vietnam’s public construction works
Authors: Luong Hai Nguyen , Tuan Ngo Anh 
Published: November 2022

PurposeThe planning function is a central component of management principles, enabling the success of construction project management. Many works have been highlighting the topic of critical success factors within construction organizations, yet the results have rarely covered planning behaviors within public construction work management; these less investigated areas were the aims of this study.Design/methodology/approachTo fulfill this research aim, seven attributes of planning function were first derived through focus group studies, a focused literature review and focal interviews with industry practitioners. Then, a regression analysis design was employed with data collected from 139 professionals who are involved in public construction works management in Vietnam. The structural equation modeling technique with partial least-squares estimation was utilized to analyze the data.FindingsThe results revealed seven behavioral dimensions (i.e. Goals planning (PL1), Planning guidance (PL2), Strategic planning (PL3), Financial mobilization (PL4), Action plan (PL5), Expenditure planning (PL6) and Responsibility assignment (PL7)) to measure planning function management in terms of public construction works. The study also reveals that Goals planning (PL1), Financial mobilization (PL4), Expenditure planning (PL6) and Responsibility assignment (PL7) have significant effects on management effectiveness. At the same time, Goals planning (PL1) acts as the mediator of Planning guidance (PL2) and Strategic planning (PL3); while Action plan (PL5) specifies an indirect influence through the mediator of PL4, PL6 and PL7.Originality/valueThe success of this approach is expected to reinforce the contribution of the planning function and suggest a useful tool for supporting the professionals in managing public construction works.
Differences in financial inclusion by disability type
Authors: Wann Christi R. , Burke-Smalley Lisa 
Published: November 2022

PurposeThe purpose of this study is to determine the nature of financial inclusion for individuals with various types of disabilities.Design/methodology/approachData from 2015, 2017 and 2019 FDIC Survey of Household Use of Banking and Financial Services was pooled, and binary logistic regressions were used to investigate differences in barriers to financial inclusion (e.g. unbanked) between people with different types of disabilities (e.g. cognitive) and those without such disabilities.FindingsUsing five separate barrier measures, the authors found specific disability types face different barriers to financial inclusion. For example, respondents with cognitive, ambulatory or two or more disabilities were more likely to use nonbank transaction products and alternative financial services. And, those with vision or cognitive disabilities were more likely to be denied or receive reduced credit. When examining aggregate barriers to financial inclusion (total number of barriers faced) respondents with cognitive, ambulatory, hearing or two or more disabilities experienced the lowest degree of financial inclusion in the authors’ dataset.Research limitations/implicationsCausal inference cannot be made due to the cross-sectional nature of the data. The data only covers the US population, and the measurement of disability type could include those with short-term impairments. Further, there may be an omitted variable bias.Practical implicationsBest practices to maximize financial inclusion for those with different disability types should address accessibility issues, bank staff education, financial literacy education and poverty issues. Additional government policies and oversight are also needed to protect and enhance the overall financial inclusion of people with disabilities.Originality/valueTo the best of the authors’ knowledge, this paper is the first to examine the relationship between various barriers to financial inclusion and aggregate barriers to financial inclusion by disability type. Specific disability types are found to face different barriers to financial inclusion.
“Connected we stand, disconnected we fall”. Analyzing the importance of digital platforms in transnational supply chain management
Authors: Marrucci Anna , Rialti Riccardo , Donvito Raffaele , Syed Faheem Uddin 
Published: November 2022

PurposeThis study seeks to explore the importance of digital platforms in restoring global supply chains interrupted by the coronavirus pandemic. Specifically, the research focuses on internally developed digital platforms and their potential to ensure supply chain continuity between developed and emerging markets.Design/methodology/approachMultiple comparative case studies have been selected for the research methodology. Eight cases concerning digital platform implementation for global SC management – four from developed countries and four from emerging markets – have been selected. The four pairs of cases represent four global supply chain mechanisms.FindingsThe results revealed that the use of internally developed digital platforms serves as a quick solution for immediate problems caused by ripple effects in global supply chain and negative environmental conditions. Digital platforms could therefore facilitate reciprocal monitoring and information exchanges between SC partners in different countries.Originality/valueThe digital platform research stream is in its early stages. Research thus far has mostly focused on externally developed digital platforms managed by an orchestrator. The platforms' usefulness in the dialogue between developed and emerging markets requires further exploration.
Pay attention to me! The role of endorsements, patents, gender and prior experience in startup media attention
Authors: Gasiorowski Laura , Lee Ahreum 
Published: November 2022

PurposeThe purpose of this paper is to explore the antecedents of media attention in the context of early-stage startups. While many studies have examined the implications of media attention on firm outcomes, few have investigated the antecedents especially in the context of early-stage startups who significantly lack organizational legitimacy. This study attempts to answer an important and yet unanswered question: What type of startups are more likely to be covered by the media?Design/methodology/approachUsing Poisson regression, the authors analyze all media articles written about 315 early-stage ventures in the USA.FindingsThe authors found that startups with a prestigious investor or a patent have more media attention and startups with a female founder or prior entrepreneurial experience have less. The results suggest that entrepreneurial signals do play a role in media attention, but that the signal–signaler relationship may be more complicated than that in the investment literature.Practical implicationsEntrepreneurs may benefit from signaling less noisy and unambiguous signals that the media pays more attention to, such as getting an endorsement from reputable third parties early on, which might activate noisy signals.Originality/valueThe contribution of this paper is to extend the current literature on media attention and entrepreneurship by shedding light on attributes of startups that may help or hurt the volume of media attention in an uncertain and noisy environment.
A contextualized study of blockchain technology adoption as a digital currency platform under sanctions
Authors: Ronaghi Mohammad Hossein 
Published: November 2022

PurposeThe blockchain technology is based on distributed ledger. Many stakeholders, such as developers, entrepreneurs and technology lovers, consider the blockchain as an economic and business re-creation that is faced with numerous challenges in its application. Blockchain technology is the backbone of many digital currencies, i.e. Bitcoin and Ethereum. Although presently digital currencies are recognized as payment and exchange instruments in many countries, the economic sanctions imposed on some countries have restricted the possibility of the trading. So, this study seeks to evaluate the adoption of blockchain for digital currency use in Iran in the shadow of economic sanctions.Design/methodology/approachThe developed value-based technology adoption model and smart PLS software have been used in this research. The statistical population of the study was people active in the Iranian stock market; the purpose for this selection was their familiarity with financial and digital currency issues.FindingsThe results show that the terms of sanctions, usage and facilitating conditions are directly related to users' perceived value of digital currency and its use; As a result, in a sanctioned country like Iran, the use of digital currencies is being accepted as a way of rolling out economic sanctions and thus making commercial payments.Originality/valueAs well as the fact that evaluating the adoption of the blockchain technology in a sanctioned country like Iran is considered as the originality aspect of the research, applying an extended model in the technology adoption is also the research innovation.
Interscalar maintenance: configuring an Indigenous ‘premium carbon product’ in northern Australia (and beyond)
Authors: Neale Timothy 
Published: November 2022

AbstractMitigating climate change requires us to constrain combustion in a double sense: decreasing both the use of fossil fuels and the flammability of the biosphere. Fire management by Indigenous peoples in Australia's northern savannas has been presented as a solution to offset the former and assist with the latter, leading to the foundation of a regional economy of projects generating ‘premium’ carbon credits on Indigenous lands. This article attends to the translational zone – predominantly made up of non‐Indigenous white professionals – that functions to configure the ‘right story’ of these credits across diverse epistemes and contexts. Following such commodities’ interscalar connections, I suggest, helps illustrate the contingencies and contradictions produced by tradeable carbon, as individuals and organizations seek to maintain a niche within a changing climate and shifting global atmospheric relations.