bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Multi-Ancestry Polygenic Risk Score for Coronary Heart Disease Based on an Ancestrally Diverse Genome-Wide Association Study and Population-Specific Optimization
Authors: Smith Johanna L. , Tcheandjieu Catherine , Dikilitas Ozan , Iyer Kruthika , Miyazawa Kazuo , Hilliard Austin , Lynch Julie , Rotter Jerome I. , Chen Yii-Der Ida , Sheu Wayne Huey-Herng , Chang Kyong-Mi , Kanoni Stavroula , Tsao Phil , Ito Kaoru , Kosel Matthew , Clarke Shoa L. , Schaid Daniel J. , Assimes Themistocles L. , Kullo Iftikhar J. 
Published: June 2023

AbstractBackgroundPredictive performance of polygenic risk scores (PRS) varies across populations. To facilitate equitable clinical use, we developed PRS for coronary heart disease (PRSCHD) for 5 genetic ancestry groups.MethodsWe derived ancestry-specific and multi-ancestry PRSCHDbased on pruning and thresholding (PRSP+T) and continuous shrinkage priors (PRSCSx) applied on summary statistics from the largest multi-ancestry genome-wide meta-analysis for CHD to date, including 1.1 million participants from 5 continental populations. Following training and optimization of PRSCHDin the Million Veteran Program, we evaluated predictive performance of the best performing PRSCHDin 176,988 individuals across 9 cohorts of diverse genetic ancestry.ResultsMulti-ancestry PRSP+Toutperformed ancestry specific PRSP+Tacross a range of tuning values. In training stage, for all ancestry groups, PRSCSxperformed beter than PRSP+Tand multi-ancestry PRS outperformed ancestry-specific PRS. In independent validation cohorts, the selected multi-ancestry PRSP+Tdemonstrated the strongest association with CHD in individuals of South Asian (SAS) and European (EUR) ancestry (OR per 1SD[95% CI]; 2.75[2.41-3.14], 1.65[1.59-1.72]), followed by East Asian (EAS) (1.56[1.50-1.61]), Hispanic/Latino (HIS) (1.38[1.24-1.54]), and weakest in African (AFR) ancestry (1.16[1.11-1.21]). The selected multi-ancestry PRSCSxshowed stronger association with CHD in comparison within each ancestry group where the association was strongest in SAS (2.67[2.38-3.00]) and EUR (1.65[1.59-1.71]), progressively decreasing in EAS (1.59[1.54-1.64]), HIS (1.51[1.35-1.69]), and lowest in AFR (1.20[1.15-1.26]).ConclusionsUtilizing diverse summary statistics from a large multi-ancestry genome-wide meta-analysis led to improved performance of PRSCHDin most ancestry groups compared to single-ancestry methods. Improvement of predictive performance was limited, specifically in AFR and HIS, despite use of one of the largest and most diverse set of training and validation cohorts to date. This highlights the need for larger GWAS datasets of AFR and HIS individuals to enhance performance of PRSCHD.
Graph representations of iEEG data for seizure detection with graph neural networks
Authors: Díaz-Montiel Alan A. , Lankarany Milad 
Published: June 2023

ABSTRACTEpilepsy is a neurological disorder that affects over 50 million individuals worldwide. Today, the gold-standard treatment for those who are drug resistant, meaning that symptoms cannot be controlled with medication, is to surgically remove the seizure onset zone (SOZ), the area of the brain believed to cause seizures: the main symptom of epilepsy. Unfortunately, around 50% of drug resistant patients are not resective candidates, which can be attributed in part to poor SOZ localization. SOZ localization is a complex and lengthy procedure, requiring visual inspection and manual processing by human experts that first need to localize and isolate seizure events. The intracranial electroencephalography (iEEG) is a tool that records electrophysiological activity of the inner brain at different regions and depths, and provides critical information on the SOZ. However, iEEG data processing methodologies are not standardized, and practice and resources vary across hospitals and clinics. To assist human experts with systematic processing of iEEG data, we propose a data processing pipeline that generates graph representations of iEEG data. We evaluate 9 different graph representations of publicly available iEEG data from 25 patients with epilepsy with a graph neural network model trained to detect seizures. Our results suggest that graph representations of iEEG data that leverage electrode and functional connectivity features are powerful data structures to analyze and interpret iEEG data in the context of epilepsy. We anticipate that our data pipeline that provides a systematic processing of neural data with graphs can integrate other data modalities like neuroimaging data. Moreover, methods used in the data pipeline have potentials to apply to other neurological disorders such as Parkinson’s disease or major depression disorder.
Forecasting fish recruitment using machine learning methods: A case study of arabesque greenling
Authors: Okamura Hiroshi , Morita Shoko , Kuroda Hiroshi 
Published: June 2023

AbstractFish recruitment prediction is a central topic in fisheries science. We use a machine learning method for predicting the recruitment of Arabesque greenling in Hokkaido, Japan. Biological, fisheries-related, and environmental factors were included in the predictive models as feature variables. A gradient boosting model (GBM) showed better predictive performance compared with a linear regression model (LRM) and a random forest model (RFM) in terms of relative bias and relative root mean square error for recruitment prediction in the last 5 years. The most influential feature for GBM was spawning stock biomass in the last year, followed by the fishing rate for older fish. The sea surface temperature (SST) was a very weak predictor in the GBM but was the most influential feature in the LRM. The difference among models suggests the importance of nonlinearity and variable interactions. Machine learning methods will greatly contribute to fish recruitment forecast and thereby sustainable fisheries management.
A novel deep proteomic approach in human skeletal muscle unveils distinct molecular signatures affected by aging and resistance training
Authors: Roberts Michael D. , Ruple Bradley A. , Godwin Joshua S. , McIntosh Mason C. , Chen Shao-Yung , Kontos Nicholas J. , Agyin-Birikorang Anthony , Michel J. Max , Plotkin Daniel L. , Mattingly Madison L. , Mobley C. Brooks , Ziegenfuss Tim N. , Fruge Andrew D. , Kavazis Andreas N. 
Published: June 2023

ABSTRACTWe examined the myofibrillar (MyoF) and non-myofibrillar (non-MyoF) proteomic profiles of the vastus lateralis (VL) muscle of younger (Y, 22±2 years old; n=5) and middle-aged participants (MA, 56±8 years old; n=6), and MA following eight weeks of knee extensor resistance training (RT, 2d/week). Shotgun/bottom-up proteomics in skeletal muscle typically yields wide protein abundance ranges that mask lowly expressed proteins. Thus, we adopted a novel approach whereby the MyoF and non-MyoF fractions were separately subjected to protein corona nanoparticle complex formation prior to digestion and Liquid Chromatography Mass Spectrometry (LC-MS) analysis. A total of 10,866 proteins (4,421 MyoF and 6,445 non-MyoF) were identified. Across all participants, the number of non-MyoF proteins detected averaged to be 5,645±266 (range: 4,888–5,987) and the number of MyoF proteins detected averaged to be 2,611±326 (range: 1,944–3,101). Differences in the non-MyoF (8.4%) and MyoF (2.5%) proteome were evident between age cohorts. Further, most of these age-related non-MyoF proteins (447/543) were more enriched in MA versus Y. Several biological processes in the non-MyoF fraction were predicted to be operative in MA versus Y including (but not limited to) increased cellular stress, mRNA splicing, translation elongation, and ubiquitin-mediated proteolysis. Non-MyoF proteins associated with splicing and proteostasis were further interrogated, and in agreement with bioinformatics, alternative protein variants, spliceosome-associated proteins (snRNPs), and proteolysis-related targets were more abundant in MA versus Y. RT in MA non-significantly increased VL muscle cross-sectional area (+6.5%, p=0.066) and significantly increased knee extensor strength (+8.7%, p=0.048). However, RT modestly altered the MyoF (∼0.3%, 11 upregulated and two downregulated proteins) and non-MyoF proteomes (∼1.0%, 56 upregulated and eight downregulated proteins, p<0.01). Further, RT did not affect predicted biological processes in either fraction. Although participant numbers were limited, these preliminary results using a novel deep proteomic approach in skeletal muscle suggest that aging and RT predominantly affects protein abundances in the non-contractile protein pool. However, the marginal proteome adaptations occurring with RT suggest either: a) this may be an aging-associated phenomenon, b) more rigorous RT may stimulate more robust effects, or c) RT, regardless of age, subtly affects skeletal muscle protein abundances in the basal state.
Temporally specific gene expression and chromatin remodeling programs regulate a conservedPdynenhancer
Authors: Phillips Robert A. , Wan Ethan , Tuscher Jennifer J. , Reid David , Drake Olivia R. , Ianov Lara , Day Jeremy J. 
Published: June 2023

SummaryNeuronal and behavioral adaptations to novel stimuli are regulated by temporally dynamic waves of transcriptional activity, which shape neuronal function and guide enduring plasticity. Neuronal activation promotes expression of an immediate early gene (IEG) program comprised primarily of activity-dependent transcription factors, which are thought to regulate a second set of late response genes (LRGs). However, while the mechanisms governing IEG activation have been well studied, the molecular interplay between IEGs and LRGs remain poorly characterized. Here, we used transcriptomic and chromatin accessibility profiling to define activity-driven responses in rat striatal neurons. As expected, neuronal depolarization generated robust changes in gene expression, with early changes (1 h) enriched for inducible transcription factors and later changes (4 h) enriched for neuropeptides, synaptic proteins, and ion channels. Remarkably, while depolarization did not induce chromatin remodeling after 1 h, we found broad increases in chromatin accessibility at thousands of sites in the genome at 4 h after neuronal stimulation. These putative regulatory elements were found almost exclusively at non-coding regions of the genome, and harbored consensus motifs for numerous activity-dependent transcription factors such as AP-1. Furthermore, blocking protein synthesis prevented activity-dependent chromatin remodeling, suggesting that IEG proteins are required for this process. Targeted analysis of LRG loci identified a putative enhancer upstream ofPdyn(prodynorphin), a gene encoding an opioid neuropeptide implicated in motivated behavior and neuro-psychiatric disease states. CRISPR-based functional assays demonstrated that this enhancer is both necessary and sufficient forPdyntranscription. This regulatory element is also conserved at the humanPDYNlocus, where its activation is sufficient to drivePDYNtranscription in human cells. These results suggest that IEGs participate in chromatin remodeling at enhancers and identify a conserved enhancer that may act as a therapeutic target for brain disorders involving dysregulation ofPdyn.
Almond rhizosphere viral, prokaryotic, and fungal communities differed significantly among four California orchards and in comparison to bulk soil communities
Authors: ter Horst Anneliek M. , Adebiyi Temiloluwa V. , Hernandez Daisy A. , Fudyma Jane D. , Emerson Joanne B. 
Published: June 2023

AbstractCharacterization of rhizosphere microbiomes and their interactions is essential to a holistic understanding of plant health in support of sustainable agriculture. Viruses are a key, understudied component of rhizosphere microbiomes, with potential impacts on both plant-beneficial and -pathogenic organisms through infection. In this study, we sampled rhizospheres and bulk soils associated with 15 almond trees in four California orchards and generated viromic, 16S rRNA gene, and ITS1 amplicon sequencing datasets to compare viral, prokaryotic, and fungal communities. In total, 10,440 viral operational taxonomic units (vOTUs), 16,146 bacterial and archaeal OTUs, and 6,684 fungal OTUs were recovered. All three community types differed most significantly among the four orchards and secondarily between bulk and rhizosphere soils. Despite compositional differences, no significant differences in richness were observed between bulk and rhizosphere soils for any of the studied biota. Overall, viruses, prokaryotes, and fungi shared similar beta-diversity patterns in almond rhizospheres and bulk soils on a regional scale, counter to recently observed decoupling between viral and prokaryotic community biogeographic patterns in a variety of bulk soils.
High-throughput confocal airy beam oblique light-sheet tomography of brain-wide imaging at single-cell resolution
Authors: Qi Xiaoli , Muñoz-Castañeda Rodrigo , Narasimhan Arun , Ding Liya , Chen Xin , Elowsky Corey , Palmer Jason , Drewes Rhonda , Sun Jianjun , Mizrachi Judith , Peng Hanchuan , Wu Zhuhao , Osten Pavel 
Published: June 2023

AbstractBrain research is an area of research characterized by its cutting-edge nature, with brain mapping constituting a crucial aspect of this field. As sequencing tools have played a crucial role in gene sequencing, brain mapping largely depends on automated, high-throughput and high-resolution imaging techniques. Over the years, the demand for high-throughput imaging has scaled exponentially with the rapid development of microscopic brain mapping. In this paper, we introduce the novel concept of confocal Airy beam into oblique light-sheet tomography named CAB-OLST. We demonstrate that this technique enables the high throughput of brain-wide imaging of long-distance axon projection for the entire mouse brain at a resolution of 0.26 μm × 0.26 μm × 1.06 μm in 58 hours. This technique represents an innovative contribution to the field of brain research by setting a new standard for high-throughput imaging techniques.
Comparison of Gastric Alimetry®body surface gastric mapping versus electrogastrography spectral analysis
Authors: Schamberg Gabriel , Calder Stefan , Varghese Chris , Xu William , Wang William Jiaen , Ho Vincent , Daker Charlotte , Andrews Christopher N. , O’Grady Greg , Gharibans Armen A. 
Published: June 2023

AbstractElectrogastrography (EGG) non-invasively evaluates gastric motility but is viewed as lacking clinical utility. Gastric Alimetry® is a new diagnostic test that combines high-resolution body surface gastric mapping (BSGM) with validated symptom profiling, with the goal of overcoming EGG’s limitations. This study directly compared EGG and BSGM to define performance differences in spectral analysis. Comparisons between Gastric Alimetry BSGM and EGG were conducted by protocolized evaluation of 178 subjects (110 controls; 68 nausea and vomiting (NVS) and/or type 1 diabetes (T1D)). Comparisons followed standard methodologies for each test (pre-processing, post-processing, analysis), with statistical evaluations for group-level differences, symptom correlations, and patient-level classifications. BSGM showed substantially tighter frequency ranges vs EGG in controls. Both tests detected rhythm instability in NVS, but EGG showed opposite frequency effects in T1D. BSGM showed an 8x increase in the number of significant correlations with symptoms. BSGM accuracy for patient-level classification was 0.78 for patients v. controls and 0.96 as compared to blinded consensus panel; EGG accuracy was 0.54 and 0.43. EGG detected group-level differences in patients, but lacked symptom correlations and showed poor accuracy for patient-level classification, explaining EGG’s limited clinical utility. BSGM demonstrated substantial performance improvements across all domains.
COVID-19 shock in the hospitality industry: its effect on hotel operations within the Bono region of Ghana
Authors: Deri Mildred Nuong , Ari Ragavan Neethiahnanthan , Niber Augustine , Zaazie Perpetual , Akazire David Anandene , Anaba Martha , Andaara Dorlaar 
Published: June 2023

PurposeThe COVID-19 pandemic has long-lasting effects that necessitate business revision, innovation, and transformation in the hospital industry. The research in this field is, however, still incredibly underdeveloped. Hotels have faced unprecedented pressure due to the outbreak of novel COVID-19, forcing many to close temporarily or permanently. The aim of this study is to assess COVID-19 effect on hotels within the Bono region of Ghana, as the protocols are currently relaxed.Design/methodology/approachUsing a quantitative approach, a stratified and purposive sampling method was used and 174 hotel managers in the Bono region responded to the research questions in relation to how their businesses were affected by the COVID-19 pandemic.FindingsThe findings showed that the most prominent and recurring measures among hotels are the application of hygiene standards, employee training and awareness, reduction of employees’ guest contact and ensuring a safer environment for both guests and employees.Research limitations/implicationsThe study’s sample frame covers hotels in the Bono region of Ghana with lower star classifications, ranging from affordable to three stars in quality and service. Hotels should emphasize the importance of providing their personnel with ongoing training and education to prepare them to deal with the outbreak of the pandemic.Practical implicationsAs a result, the study suggests that hotel operators give innovative, fascinating and delightful accommodation experiences that may boost customers’ authentic happiness, as well as offer possibilities for customers to gain positive, memorable experiences from their experience.Social implicationsAcademia and hotel managers need to contribute to theory development in hotel marketing by analyzing changes in customer expectations and industry recovery measures to affect good changes in industry best practices in the aftermath of the epidemic.Originality/valueThis study makes a significant contribution to the body of knowledge of the service delivery system model research because it is one of the initial studies to examine hotel business operations and activities during the COVID-19 utilizing the Bono region as a case. Theoretical, managerial and policy implications are discussed to cope with this crisis.
Street art and creative place-making: urban tourism regeneration in Toronto, Canada
Authors: McClinchey Kelley A. 
Published: June 2023

Purpose
This paper aims to discuss the place-making processes of street art within the context of Toronto, Canada, and potential for street art as alternative tourism to contribute to new urban tourism and encourage urban regeneration in the city.

Design/methodology/approach
The study applies reflexive thematic analysis to analyse secondary data sources such as reports, maps, videos, websites, news articles and official documents alongside photographic documentation and field research.

Findings
Street art in Toronto has been found to coincide closely with processes of creative place-making. While there is some indication that municipal street art organizations and destination marketing organizations are aware of the possibilities for street art to contribute to tourism in the city, it remains an untapped resource for new urban tourism. As a component of creative place-making, it has great potential as a form of alternative tourism to regenerate a still struggling tourism economy.

Originality/value
This paper explores the nascent research area and practical application of street art as an alternative form of urban tourism in Toronto, Canada. It also fills a gap by connecting the concept of creative place-making with street art, urban regeneration and tourism specifically; a focus that needs wider attention.
Public service leadership: follower interpersonal communication satisfaction in transformational leadership and growth satisfaction, job stress and burnout
Authors: Rajesh J. Irudhaya , Prikshat Verma , Kirk Susan , Saeed Muhammad Mohtsham , Patel Parth , Sheheryar Khan Malik Muhammad 
Published: June 2023

PurposeThis study aims to explore how transformational leaders enhance public service employees’ growth satisfaction in the job and mitigate job stress and burnout, incorporating follower interpersonal communication satisfaction with the leader (IPCSL) as a mediator.Design/methodology/approachOn the basis of the survey data collected from the Indian public service employees, regression analysis, bootstrapping and SOBEL test are used to test the proposed research model.FindingsThe findings highlighted a partial mediation of follower interpersonal communication satisfaction with leader between transformational leadership (TL) and public service employees’ growth satisfaction in the job. Although there was no significant direct effect of TL on job stress and burnout, the results underlined a significant indirect effect of follower IPCSL.Originality/valueBy examining the important role of follower IPCSL, this study unravels the precise intervening mechanism between TL and follower affective outcomes like growth satisfaction in job, job stress and burnout among public service employees.
A contemplative overview of smart communities: a hybrid analytical approach
Authors: Sakshi Surabhi , Srivastava Praveen Ranjan , Mangla Sachin K. , Singh Amol 
Published: June 2023

PurposeThis study aims to uncover and develop explicit knowledge of existing smart communities (SCs) to guide services and business solutions for enterprises and serve community users in a well-thought-out manner. These sagacious frameworks will assist in analyzing trends and reaching out to pre-existing setups with different degrees of expertise.Design/methodology/approachA systematic overview is provided in this paper to unify insights and competencies toward building SCs; a hybrid analytical approach is used consisting of machine learning and bibliometric analysis. Scopus and Web of Science (WoS) are the primary databases for this purpose.FindingsSCs implement cutting-edge technologies to enhance mobility, elevating information and communication technology (ICT) skills and data awareness while improving business processes and efficiency. This system of SC is an evolution of the conventional method. It provides a foundation for intelligent community services based on individual users and technologies such as the Internet of Things (IoT), artificial intelligence, cloud computing and big data. Manufacturing-based, service-based, retail-based, resource management and infrastructure-based SCs exist in the literature.Originality/valueThe paper summarizes a conceptual framework of SCs based on existing works around SCs. To the best of the authors’ knowledge, this is the first systematic literature review that uses a hybrid approach of topic modeling and bibliometric analysis to understand SCs better.