bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spectrum of thoracic systemic venous abnormalities using multidetector computed tomography
Authors: Shehata Samar , Abdulmonaem Ghada , Gamal Aya , Assy Mostafa 
Published: April 2022

Abstract
Background
Anomalies of the thoracic systemic venous return vary widely and range from those with completely normal physiology to severe right to left shunting thus requiring surgical correction. The aim of the study is to enhance the awareness of multidetector computed tomography (MDCT) role in evaluation of systemic venous abnormalities, and be familiar with the imaging characteristics of even the extremely rare abnormalities.

Results
Among 270 examined patients, 15.19% had systemic venous abnormalities. Inferior vena cava (IVC) congenital anomalies accounted for (24.4%) of the detected abnormalities (prevalence: 3.7% among the studied population) where IVC interruption with azygos continuation was the most common detected IVC abnormality accounting for 17.7% of the detected abnormalities (prevalence: 2.6%), while IVC thrombosis accounted for 21.9% (prevalence: 3.3%). Persistent left sided superior vena cava (SVC) accounted for 14.6% of the detected abnormalities (prevalence: 2.2%), while SVC syndrome represented 19.5% (prevalence: 2.9%) and SVC aneurysm represented 2.4% (prevalence: 0.37%). Retroaortic brachiocephalic vein (BCV) and BCV thrombosis accounted for 7.3% each (prevalence: 1.1). Finally, persistent levo-atrial cardinal vein represented 2.4% of the detected abnormalities (prevalence: 0.37%).

Conclusions
MDCT is a non-invasive modality that can provide detailed information about the systemic thoracic veins before surgical or interventional procedures, especially in patients with congenital anomalies.
An exploratory case study investigating the implementation of a novel knowledge translation strategy in a pandemic: the Pandemic Practice Champion
Authors: Stevens Bonnie , Bueno Mariana , Rao Megha , Almeida Christabelle , Cotic Anna , Streitenberger Laurie , Fleming-Carroll Bonnie , Breen-Reid Karen 
Published: April 2022

Abstract
Background
The clinical Pandemic Practice Champion (PPC) role was created in a large tertiary pediatric hospital as a knowledge translation (KT) strategy for implementing COVID-19 evidence-based knowledge. We aimed to describe the core components of the PPC role, the process of implementing the role, and the factors that hindered or facilitated role implementation.

Methods
An exploratory case study was undertaken. Semi-structured interviews were conducted virtually with stakeholders including PPC, managers, and front-line health care professionals (HCP). A directed approach to qualitative content analysis consistent with the Consolidated Framework for Implementation Research (CFIR) guided the analytic process. Inductive analyses and three stages of thematic synthesis were also conducted.

Results
Four PPC, 3 managers, and 6 HCP were interviewed. The core components of the PPC role consisted of (a) acting as knowledge experts and educators, (b) problem-solving for complex patient care issues, (c) conducting crisis management, and (d) acting as a resource to management, HCP, and families. Facilitators for successful implementation included access to external information, a supportive organizational context and culture, dedicated time and resources, and leadership support. Lack of clarity of role definition, insufficient time, pandemic uncertainty and fatigue, inability to change infrastructure, and access to external information hindered implementation.

Conclusion
The PPC role was successfully implemented within a crisis context. Key barriers (role clarity, time, resources) and facilitators (organizational and leadership support) need to be considered when implementing the PPC role in practice. Future studies are needed to determine the intervention effectiveness of the champion role in changing HCP behavior and health outcomes and further examine implementation processes and mechanisms.
Changing Trends in Estrogen Receptors/Progesterone Receptors/Human Epidermal Growth Factor Receptor 2 Prevalence Rates Among Jordanian Patients With Breast Cancer Over the Years
Authors: Alsughayer Anas M. , Dabbagh Tamara Z. , Abdel-Razeq Rashid H. , Al-Jussani Ghada N. , Alhassoon Salam , Sughayer Maher A. 
Published: April 2022

PURPOSEEstrogen receptors (ERs), progesterone receptors (PRs), and human epidermal growth factor receptor 2 (HER2) are the mainstay of breast cancer management, and their prevalence rates vary among different populations possibly related to ethnic/genetic and/or socioeconomic status. In a previous study conducted at the King Hussein Cancer Center (published 2006), Jordan ER/PR/HER2 rates for patients diagnosed in 2003-2004 were 50.8%/57.5%/17.5%, respectively. The aim of this study is to revisit the prevalence rates to see if they have changed over the years with changing socioeconomic status.MATERIALS AND METHODSWe retrieved clinicopathologic data of all patients (1,185) diagnosed with breast cancer during 2018. The data included age, histologic type, grade, and ER/PR/HER2 status as determined by immunohistochemistry and/or fluorescence in situ hybridization for HER2.RESULTSThe mean age of patients was 52 (median = 51, range = 25-92) years, and the majority (73.2%) had invasive carcinoma of no special type. ER/PR/HER2 were 77.0%/72.4%./23.8%, respectively. Triple-negative breast cancers were 10.1%. In comparison with previous results of 2006, the changes are statistically significant. Similar changes were seen in other Middle Eastern populations. The current rates are close to those of Western populations.CONCLUSIONRates of ER/PR/HER2 expression have significantly changed and are close to those of Western populations for ER/PR. We propose that such changes are secondary to the adoption of a westernized lifestyle and socioeconomic changes.
Characterizing the Effects of Nasal Prong Interfaces on Aerosol Deposition in a Preterm Infant Nasal Model
Authors: Bass Karl , Momin Mohammad A. M. , Howe Connor , Aladwani Ghali , Strickler Sarah , Kolanjiyil Arun V. , Hindle Michael , DiBlasi Robert M. , Longest Worth 
Published: April 2022

Abstract
The objective of this study was to characterize the effects of multiple nasal prong interface configurations on nasal depositional loss of pharmaceutical aerosols in a preterm infant nose-throat (NT) airway model. Benchmark in vitro experiments were performed in which a spray-dried powder formulation was delivered to a new preterm NT model with a positive-pressure infant air-jet dry powder inhaler using single- and dual-prong interfaces. These results were used to develop and validate a computational fluid dynamics (CFD) model of aerosol transport and deposition in the NT geometry. The validated CFD model was then used to explore the NT depositional characteristic of multiple prong types and configurations. The CFD model highlighted a turbulent jet effect emanating from the prong(s). Analysis of NT aerosol deposition efficiency curves for a characteristic particle size and delivery flowrate (3 µm and 1.4 L/min (LPM)) revealed little difference in NT aerosol deposition fraction (DF) across the prong insertion depths of 2–5 mm (DF = 16–24%) with the exception of a single prong with 5-mm insertion (DF = 36%). Dual prongs provided a modest reduction in deposition vs. a single aerosol delivery prong at the same flow for insertion depths < 5 mm. The presence of the prongs increased nasal depositional loss by absolute differences in the range of 20–70% compared with existing correlations for ambient aerosols. In conclusion, the use of nasal prongs was shown to have a significant impact on infant NT aerosol depositional loss prompting the need for prong design alterations to improve lung delivery efficiency.
Graphical Abstract
The Causal Relationships Between Sleep-related Phenotypes and Body Composition: A Mendelian Randomized Study
Authors: Chen Yujing , Li Chun’e , Cheng Shiqiang , Pan Chuyu , Zhang Huijie , Zhang Jingxi , Zhang Zhen , Yao Yao , Cheng Bolun , Liu Li , Meng Peilin , Yang Xuena , Jia Yumeng , Wen Yan , Zhang Feng 
Published: April 2022

Abstract

Background
Despite cumulative evidence showing obesity is associated with changes in sleep quality and quantity, the study about the relationships between sleep and body composition is scarce, and whether the relationship is causal remains unknown. In this study, we examined whether there are causal associations between sleep and body composition.

Methods
First, we estimated genetic correlations between sleep-related phenotypes and body composition using the linkage disequilibrium score regression (LDSC). Mendelian randomization (MR) analysis was then conducted to test 2-way causal relationships on phenotypes with significant genetic associations. Finally, Bayesian colocalization (COLOC) analysis was performed to calculate the posterior probability of causal variation and identify the common genes to verify the results of MR.

Results
For the LDSC analysis, we observed some significant genetic correlations (rG), such as snoring and right leg fat mass (rG = 0.376, P = 7.21 × 10−80). For the MR analysis, we identified some significant causal relationships, such as snoring is the causal risk factor for whole-body fat-free mass (Pweighted median = 1.28 × 10−6, PMR-PRESSO = 1.35 × 10−7), dozing is the causal risk factor for right leg fat mass (Pweighted median = 9.22 × 10−4, PMR-PRESSO = 9.55 × 10−4), and right arm fat mass (Pweighted median = 1.11 × 10−40, PMR-PRESSO = 4.93 × 10−55) is the causal risk factor for snoring. For the COLOC analysis, we identified rs143384 mapping on GDF5 and 6 overlapped single nucleotide polymorphisms (eg, rs1421085, rs11642015) mapping on FTO.

Conclusion
Our study identified the causal relationships between sleep-related phenotypes and body composition. These findings may give insights into the mechanism of sleep disturbances and provide novel therapeutic targets.
1,2-Rearrangement from o-Quinols to Multisubstituted Catechols via Retro Diels-Alder Reaction of o-Quinol Dimers
Authors: Hashimoto Riichi , Hanaya Kengo , Sugai Takeshi , Higashibayashi Shuhei 
Published: April 2022

Abstract
The 1,2-rearrangement of o-quinols has been a long-standing unsolved problem since 1958. Although the rearrangement is expected to be useful for syntheses of catechol derivatives, it is hampered by many competing reactions and has not been developed as a useful methodology. Here, we succeeded in settling this problem by a first systematic thorough investigation, establishing the 1,2-rearrangement as a cascade reaction with a retro Diels-Alder reaction from o-quinol dimers. This is a useful strategy for syntheses of substituted catechols used as synthetic building blocks for bioactive compounds and material molecules. o-Quinol dimers were synthesized by improved oxidative hydroxylation of substituted phenols followed by spontaneous Diels-Alder reaction. The dimers then underwent the retro Diels-Alder reaction to regenerate the o-quinols followed by 1,2-rearrangement under neutral heating conditions at an appropriate temperature depending on the migratory substituent, furnishing substituted catechols in good yields. The competing reactions such as an elimination of a substituent or α-ketol rearrangement were minimized by controlling the reaction temperature.
Comparison of Physical Activity Environments in Michigan Home-Based and Licensed Childcare Programs
Authors: Clevenger Kimberly A. , Pfeiffer Karin A. 
Published: April 2022

ABSTRACT

Introduction/Purpose
Physical activity in young children is influenced by the childcare physical activity environment. Identifying differences between home-based programs and licensed centers can inform future interventions to facilitate physical activity and its benefits for all children. Our purpose was to compare the physical activity environment in home-based (n = 70) and licensed (n = 54) childcares.

Methods
Teachers/directors completed an electronic survey regarding respondent/program characteristics, the outdoor/indoor environment, and barriers to promoting physical activity. T-tests and Fisher’s exact tests compared outcomes by program type.

Results
Home-based programs had more overall (+1.5), active (+0.5), and attractive (+0.6) natural elements, and more portable or fixed (+1.9), creative fixed (+0.9), and screen time (+0.7) equipment compared with licensed centers, which were rated higher quality (+8.9 out of 50 points). Home-based programs provided more indoor time for physical activity (+2.1 min·h−1) and naptime (+3.1 min·h−1), similar outdoor and television time, longer bouts of indoor teacher-led activity (+6.1 min), and higher levels of activity while indoors (+0.5 on a scale from 1 to 7) compared with licensed centers. The most commonly reported barrier to promoting activity was cost of equipment (82.9%–87.8% of programs).

Conclusions
Despite being rated as lower quality by the state, home-based programs have many physical-activity-promoting attributes. Although some of our findings are in contrast to the extant literature, this may be due to the strong policies regarding home-based childcare programs in place in Michigan. Future research may aim to compare with other states and understand how these environmental differences impact physical activity participation.
Spatial-temporal data analysis of digital twin
Authors: He Xing , Ai Qian , Pan Bo , Tang Lei , Qiu Robert 
Published: April 2022

Background: Digital Twin (DT) has proven to be one of the most promising technologies for routine monitoring and management of complex systems with uncertainties. Methods: Our work, which is mainly concerned with heterogeneous spatial-temporal data, focuses on exploring data utilization methodology in DT. The goal of this research is to summarize the best practices that make the spatial-temporal data analytically tractable in a systematic and quantifiable manner. Some methods are found to handle those data via jointly spatial-temporal analysis in a high-dimensional space effectively. We provide a concise yet comprehensive tutorial on spatial-temporal analysis considering data, theories, algorithms, indicators, and applications. The advantages of our spatial-temporal analysis are discussed, including model-free mode, solid theoretical foundation, and robustness against ubiquitous uncertainty and partial data error. Finally, we take the condition-based maintenance of a real digital substation in China as an example to verify our proposed spatial-temporal analysis mode. Results: Our proposed spatial-temporal data analysis mode successfully turned raw chromatographic data, which are valueless in low-dimensional space, into an informative high-dimensional indicator. The designed high-dimensional indicator could capture the ’insulation’ correlation among the sampling data over a long time span. Hence it is robust against external noise, and may support decision-making. This analysis is also adaptive to other daily spatial-temporal data in the same form. Conclusions: This exploration and summary of spatial-temporal data analysis may benefit the fields of both engineering and data science.
Planar cell polarity protein-dependent basal cell height in the later stage embryonic mouse epidermis impacts on the shape of overlying suprabasal cells
Authors: Hobbs Carl , Formstone Caroline J. 
Published: April 2022

Background: Complex organ formation requires the coordinated morphogenesis of adjacent tissue layers. Here, a role for the planar cell polarity (PCP) proteins Fz6 and Celsr1 in generating squamous basal cells in the later stage embryonic epidermis of the mouse is reported, which impacts upon the shape of overlying suprabasal cells. Methods: The depth of the epidermis and basal layer as well as cell proliferation index was scored from immunostained wax sections taken from different mouse embryos mutant in planar cell polarity signalling and their wild-type littermates. Orientation of epidermal cell division in Celsr1 Crash/Crash mutants was determined from thick frozen immunostained sections. Immunostained wax sections of wild-type skin explants cultured using the Lumox method enabled any changes in epidermal and basal layer depth to be measured following the release of surface tension upon dissection of skin away from the whole embryo. Results: Increased numbers of columnar and cuboidal basal epidermal cells were observed in fz6 and Celsr1 mouse mutants including Celsr1 Crash/Crash which correlated with more rounded suprabasal cells and a thicker epidermis. Conclusions: Altogether these data support tissue intrinsic roles for PCP proteins in ‘outside-in’ (radial) skin architecture.
The Level of Digital Competence of Students as a Condition for the Readiness of Future Teachers to Use Digital Technologies in the Educational Process
Authors: Manuzuna E. , Horoshilova M. , Artemyeva S. 
Published: April 2022

The article analyzes Russian and foreign approaches to establishing the relationship between the level of digital competence of students as a condition for the readiness of future teachers to use digital technologies in the educational process.
The purpose of this study is to diagnose the level of digital competencies among students and interpret the data obtained.
Based on the analysis of Russian and foreign experience in the development of digital competencies among university students, a questionnaire was developed to assess the level of formation of digital skills and abilities. Data collection was carried out through an online survey of pedagogical university students using a structured questionnaire. The data obtained allowed us to conclude that the students of the pedagogical university demonstrated a sufficiently high level of digital competence.
Future teachers demonstrated high results in such competencies as the use of digital solutions for effective communication with both teachers and students; the creation of their educational materials and assignments on subjects using a computer; modification and exchange of digital materials; the use of the Internet to search for information resources, comparison, evaluation and selection of digital resources; knowledge of the basics of digital security; the use of digital technologies at different stages of training and in the implementation of various organizational forms of training (lectures, practical classes, consultations, tests, exams, individual and group work, including on a project), including for self-organization and self-control and creative (productive) solutions of educational tasks.
ExpertRNA: A New Framework for RNA Secondary Structure Prediction
Authors: Liu Menghan , Poppleton Erik , Pedrielli Giulia , Šulc Petr , Bertsekas Dimitri P. 
Published: April 2022

Ribonucleic acid (RNA) is a fundamental biological molecule that is essential to all living organisms, performing a versatile array of cellular tasks. The function of many RNA molecules is strongly related to the structure it adopts. As a result, great effort is being dedicated to the design of efficient algorithms that solve the “folding problem”—given a sequence of nucleotides, return a probable list of base pairs, referred to as the secondary structure prediction. Early algorithms largely rely on finding the structure with minimum free energy. However, the predictions rely on effective simplified free energy models that may not correctly identify the correct structure as the one with the lowest free energy. In light of this, new, data-driven approaches that not only consider free energy, but also use machine learning techniques to learn motifs are also investigated and recently been shown to outperform free energy–based algorithms on several experimental data sets. In this work, we introduce the new ExpertRNA algorithm that provides a modular framework that can easily incorporate an arbitrary number of rewards (free energy or nonparametric/data driven) and secondary structure prediction algorithms. We argue that this capability of ExpertRNA has the potential to balance out different strengths and weaknesses of state-of-the-art folding tools. We test ExpertRNA on several RNA sequence-structure data sets, and we compare the performance of ExpertRNA against a state-of-the-art folding algorithm. We find that ExpertRNA produces, on average, more accurate predictions of nonpseudoknotted secondary structures than the structure prediction algorithm used, thus validating the promise of the approach. Summary of Contribution: ExpertRNA is a new algorithm inspired by a biological problem. It is applied to solve the problem of secondary structure prediction for RNA molecules given an input sequence. The computational contribution is given by the design of a multibranch, multiexpert rollout algorithm that enables the use of several state-of-the-art approaches as base heuristics and allowing several experts to evaluate partial candidate solutions generated, thus avoiding assuming the reward being optimized by an RNA molecule when folding. Our implementation allows for the effective use of parallel computational resources as well as to control the size of the rollout tree as the algorithm progresses. The problem of RNA secondary structure prediction is of primary importance within the biology field because the molecule structure is strongly related to its functionality. Whereas the contribution of the paper is in the algorithm, the importance of the application makes ExpertRNA a showcase of the relevance of computationally efficient algorithms in supporting scientific discovery.
Features Selection as a Nash-Bargaining Solution: Applications in Online Advertising and Information Systems
Authors: Keshanian Kimia , Zantedeschi Daniel , Dutta Kaushik 
Published: April 2022

Feature selection is a fundamental problem in online advertising, as features usually need to be purchased from third parties, and they are costly. Although many feature selection techniques can be used in online advertising and the general information systems (IS) domain, their performance is often context specific. Therefore, the literature of IS is suffering from a lack of adequate and generic methods. In this study, we address this issue by proposing a novel approach that employs ideas from the field of cooperative game theory. We derive a (continuous) second-order cone program that any convex programming solver can solve for determining the best subset of features. We show the efficacy of our proposed method on a real-life online advertising case study. We demonstrate that our proposed approach performs better in accuracy, precision, recall, and F-1 score than the best of the other approaches with much fewer features. Also, to illustrate that our method’s benefits are not limited to the context of online advertising, we perform an extensive set of simulations and consider a well-established real-life data set drawn from the UCI Machine Learning Repository at the University of California, Irvine. Summary of Contribution: Selecting the best subset of features is an important problem in the context of online advertising and, more broadly, in the field of information systems because firms usually need to buy costly data to model and forecast economic outcomes. In this study, we propose a novel methodology for addressing this problem. The proposed method employs the concept of the Nash bargaining solution in cooperative game theory to create a good balance between maximizing the fit while minimizing the noise when selecting the best subset of features. We apply the method to a real-life online advertising case study, providing superior performance in predicting and interpreting the features. Moreover, we show that the proposed method applies to a broader range of feature selection problems. We conduct a comprehensive computational study on simulated regression data sets and other real-life classification data sets widely available in the machine learning domain. The result of these efforts indicates that our method is robust in terms of prediction accuracy by outperforming several state-of-the-art techniques.