bluuebunny/crossref_metadata_2025_split huggingface dataset:
Factors influencing competitive balance across European football top tier leagues
Authors: Gasparetto Thadeu , Mishchenko Dmitry , Zaitsev Egor 
Published: December 2022

AbstractThe study aims to examine the factors impacting the competitive balance (CB) in 22 of Europe's top‐tier football leagues from 2004 to 2021. Three types of influence factors are selected: financial, economic, and sportive. The dataset has a total of 374 observations, comprising 22 countries over 17 seasons. Competitive Balance is measure by three indicators for robustness check. Six Ordinary Least Squares regression models are carried out. Our outputs evidence that play‐offs for relegation, average age, talent concentration, and standard deviation of team values showed negative effect while number of teams in the league, Elo rank, local currency to Euro rate, and Gini index have positive effect. The best level of balance is achieved with a percentage of relegated of 20.9%. Our study explains the change in CB in terms of tournament format, financial indicators, and a wide range of economic variables that have not previously been presented. The empirical results offered here may be useful for UEFA and domestic league organizers in order to improve the competitive level in the European football.
Molecular Mechanisms Associated with Protecting IEC‐6 Cells from Acrylamide‐Induced Tight Junction Damage by Ganoderma atrum Polysaccharide
Authors: Lu Jiawen , Yang Ying , Varga Elisabeth , Marko Doris , Yu Qiang , Xie Jianhua , Li Chang , Chen Yi 
Published: December 2022

ScopeThe previous in vivo studies show Ganoderma atrum polysaccharide (PSG‐F2) has a protective effect against the acrylamide (AA)‐induced intestinal oxidative damage in rats. Now, this study aims to explore the protective mechanism with IEC‐6 cell model.Methods and resultsBased on RNA Sequencing (RNA‐Seq), the study screens MAPK signaling pathway as one of the most crucial pathways for pretreatment with PSG‐F2 against AA‐induced damage in IEC‐6 cells. In total, six key MAPK signaling pathway‐related proteins (p‐P38/P38, p‐ERK/ERK, and p‐JNK/JNK), and three tight junction key proteins (Zonula Occludens protein‐1, Claudin‐1, and Occludin) are detected by Western blot and immunofluorescence, which verify the RNA‐Seq data. Moreover, PD98059 interference inhibits critical proteins in the MAPK signaling pathway, thus uncovering the precise molecular mechanisms of MAPK/ERK signaling pathway involve in the protective effects of PSG‐F2 against AA‐induced intestinal barrier damage.ConclusionThese findings confirm that PSG‐F2 can be used as a daily dietary supplement to protect the intestinal cells from damage caused by thermal processing hazards AA.
International monitoring of capacity of treatment systems for alcohol and drug use disorders: Methodology of the Service Capacity Index for Substance Use Disorders
Authors: Krupchanka Dzmitry , Formanek Tomas , Shield Kevin , Rehm Jürgen , Heymans Martijn W. , Fleischmann Alexandra , Degenhardt Louisa , Gawad Tarek , Poznyak Vladimir 
Published: December 2022

AbstractObjectivesWe aimed to develop a Service Capacity Index for Substance Use Disorders (SCI‐SUD) that would reflect the capacity of national health systems to provide treatment for alcohol and drug use disorders, in terms of the proportion of available service elements in a given country from a theoretical maximum.MethodsData were collected through the WHO Global Survey on Progress with Sustainable Development Goals (SDG) Health Target 3.5, conducted between December 2019 and July 2020 to produce the SCI‐SUD, based on 378 variables overall.ResultsThe SCI‐SUD was directly derived for 145 countries. We used multiple imputation to produce comparable SCI‐SUD estimates for countries that did not submit data (40 countries) or had very high level of missingness (9 countries). The final SCI‐SUD demonstrates considerable consistency and internal stability and is strongly associated with the macro‐level economic, healthcare‐related and epidemiologic (such as prevalence rates) variables.ConclusionThe presented methodology represents a step forward in monitoring the global situation in regard to the development of treatment systems for SU disorders, however, further work is warranted to improve the external validity of the measure (e.g., in‐depth data generation in countries) and ensure its feasibility for regular reporting (e.g., reducing the number of variables).
Development of the health literacy assessment instrument for chronic pain patients: A Delphi study
Authors: Chen Siqing , Cao Meijuan , Zhang Jing , Yang Lili , Xu Xiaolin , Zhang Xingwei 
Published: December 2022

AbstractAimTo develop health literacy assessment instrument for patients with chronic pain.DesignQualitative methods based on Delphi technique, assessed against the CREDES checklist.MethodsA 2‐round Delphi method was adopted in this study. The panel consisted of 19 experts.ResultsThe health literacy assessment instrument for chronic pain patients was constructed, which contained 3 dimensions (functional health literacy, interactive health literacy and critical health literacy) and 41 items. The positive coefficients of two rounds Delphi were 100.00% and 89.5%, respectively. The authority coefficient of experts was 0.848 and 0.858, respectively. The coordination coefficients of dimension and items were 0.222 and 0.364, respectively.ConclusionsThe health literacy assessment instrument dimensions and items for patients with chronic pain based on a Delphi method are valid. This instrument is suitable for investigating the health literacy level of patients with chronic pain.
The older adults' experiences of living in the nursing home during the COVID‐19 pandemic: A qualitative study in Iran
Authors: Asgari Zahra , Darvishpour Azar 
Published: December 2022

AbstractAimThis study aimed to describe the experiences of older adults living in a nursing home during the COVID‐19 pandemic.DesignA qualitative descriptive study.MethodsIn present study, 20 older adults living in a nursing home in Rasht, northern Iran, participated. Purposeful sampling was applied until data saturation. The qualitative content analysis was done according to the steps proposed by Zhang and Wildemuth.ResultsThe central theme was “Intensification of life problems in the nursing home”, which emerged from the 115 primary codes, 4 main categories and 7 subcategories. The main categories included “feelings about COVID‐19,” “intensification of isolation and loneliness,” “imprisonment and feeling forgotten” and “difficulty in adapting”.ConclusionQuarantine and special protocols have aggravated the hardships of life for older adults, and they experienced negative emotions in the nursing home. However, the older adults hoped that the situation would improve, and the pandemic would end.
Effect of role overload on missed nursing care in China: The role of work addiction and leader‐member exchange
Authors: Xie Lin‐Li , Jiang Wenchun , Niyomsilp Eksiri , Jing Jie , Feng Lu , Wen Yilin , Wang Li , Zheng Rongmei 
Published: December 2022

AbstractAimThe aim was to examine the effect of role overload, work addiction and leader‐member exchange on missed nursing care.DesignA cross‐sectional study.MethodsChinese registered nurses from five Sichuan province public hospitals were studied from March 2022–May 2022. The measurements were derived from a questionnaire on role overload, work addiction, missed nursing care, leader‐member exchange and a sociodemographic datasheet. Descriptive statistics and inferential statistics were conducted (N = 403).ResultsRole overload was associated with missed nursing care, and work addiction played a mediation role. Leader‐member exchange negatively predicted work addiction and played a moderating role between role overload and work addiction. The effect of role overload on work addiction was attenuated when the level of leader‐member exchange was higher. Promoting leader‐member exchange could mitigate how role overload undermines missed nursing care.
Effects of a mental health nursing simulation for general ward nurses: A pilot study
Authors: Lee Min‐Yeong , Choi Yun‐Jung 
Published: December 2022

AbstractThis study aimed to develop a mental health nursing simulation education programme for non‐psychiatric nurses and verify its effects on mental health care competence, burden, and anxiety. To verify the effects of the simulation, we applied a non‐equivalent control group pre‐posttest research design. We developed a mental health nursing simulation using a standardized patient who presented moderate levels of anxiety and depressive mood during chemotherapy after mastectomy. The participants were nurses working at non‐psychiatric wards of a general hospital in Seoul, Korea. Participants' mental health care competency scores increased by 80% in the experimental group and 15% in the control group from pre‐test to posttest. Burden scores decreased by 42% in the experimental group and 4% in the control group from pre‐test to posttest, and anxiety scores decreased by 77% in the experimental group and 24% in the control group. This study demonstrated the nursing simulation education programme's effectiveness as a complementary tool to improve mental health nursing care for non‐psychiatric nurses.
Prevalence and factors associated with academic burnout risk among nursing and midwifery students during the COVID‐19 pandemic: A cross‐sectional study
Authors: Baudewyns Véronique , Bruyneel Arnaud , Smith Pierre , Servotte Jean‐Christophe , Dancot Jacinthe 
Published: December 2022

AbstractAimThe aim of the study was to assess the prevalence of academic burnout (AB) and its associated factors among nursing and midwifery students during the COVID‐19 pandemic.DesignA correlational cross‐sectional study.MethodsAn online survey was distributed from November to December 2020 to nursing and midwifery students in Belgium. The risk of AB was assessed using the MBI‐SS Academic Burnout Inventory scale. Factors associated with AB were related to the personal life and level of education of the student and to the COVID‐19 pandemic.ResultsThe prevalence of overall AB risk was 50.0% (95% CI 48.5–53.1). Factors significantly associated with higher risk of AB were having a child, having a job, the level of academic training, working overtime, insufficient personal protective equipment against viral contamination during the last internship, work overload due to the pandemic, personal proven or possible SARS‐CoV‐2 infection and having a relative who died related to COVID‐19.
Understanding the fracture toughness of gadolinium‐ and lead‐containing plexiglass
Authors: Zhang Yujuan , Liu Xiayu , Li Yuqing , Wu Defeng , Zhang Ming 
Published: December 2022

AbstractToughened gadolinium‐ and lead‐containing plexiglasses (GLCPs) were prepared via copolymerization using ethoxylated bisphenol A dimethacrylate (BPAxEODMA, x = 2, 4, 10) as comonomer and network regulator. As‐obtained modified GLCPs possessed highly improved toughness, with satisfactory shielding and optical performances. The fracture mechanism was studied then in terms of fracture surface analyses. The results disclosed that both the impact strength and the fracture toughness (KIC) increased with the increase of fatty chain lengths or concentrations of BPAxEODMA, and the surface morphology strongly depended on the fracture processes. A morphological evolution, from mirror region to haze one, and finally to hackle region, was visible on all GLCP samples. However, the morphological characteristics of each region, such as size and roughness as well as the appearance of ring‐banded structure and firework‐like pattern, were completely different. The crack propagation mechanism was utilized to correlate the fracture surface morphology with fracture process of the samples. The relationship between KIC of the samples and their crosslinking networks was well‐built in this way. This work proposes valuable information around fabricating the anti‐radiation GLCPs with high and tailorable mechanical performance.
Polypharmacy among medicaid‐insured children with and without documented obesity
Authors: Kyler Kathryn E. , Hall Matt , Antoon James W. , Goldman Jennifer , Grijalva Carlos G. , Shah Samir S. , Tang Girdwood Sonya , Williams Derek J. , Feinstein James A. 
Published: December 2022

AbstractObjectivePolypharmacy increases the risk of drug–drug interactions and adverse drug events. As obesity and rates of obesity‐associated comorbid chronic conditions continue to rise, an improved understanding of whether children with obesity experience higher risk of polypharmacy is needed. This study aimed to compare chronic medication polypharmacy prevalence among children with and without a diagnosis of obesity.MethodsWe performed a cross‐sectional examination of prescription data for children aged 2–18 years prescribed ≥1 chronic medication using the 2019 Marketscan Medicaid database. Children with documented obesity were identified using medical visit diagnosis codes. Chronic medications included any ≥30‐day prescription with ≥2 dispensed refills. Polypharmacy was defined as the prescription of ≥2 chronic medications for ≥1 overlapping days. Chi‐squared tests compared polypharmacy prevalence and the distribution of chronic medication classes between children with and without obesity. Logistic regression determined the adjusted odds ratio (aOR) of polypharmacy for children with obesity, adjusting for relevant demographic and clinical differences.ResultsOf 634,671 included children, 12.2% had documented obesity. More than one‐half (52.7%) of children with obesity experienced polypharmacy compared with 47.6% of children without obesity (aOR 1.06 [95% confidence interval 1.04–1.08]). Chronic medication prescriptions, particularly for psychiatric and asthma medications, were more commonly prescribed among children with obesity than those without obesity.ConclusionsChildren with documented obesity have higher polypharmacy prevalence than children without obesity. Clinicians must be aware of this risk and minimize inappropriate polypharmacy whenever possible. Future work should examine the consequences of polypharmacy, including drug–drug interactions and adverse drug events in children with obesity.
Fabrication of cellulose/plant oil based flexible epoxy thermoset with excellent UV‐blocking performance
Authors: Lu Chuanwei , Wang Xinyu , Hua Wenhui , Wang Shan , Wang Shaojun , Wang Jifu , Yong Qiang , Chu Fuxiang 
Published: December 2022

AbstractFlexible epoxy thermosets have promising applications in modern industry. However, the development of next‐generation flexible epoxy thermosets with high biomass content and multi‐functions remains challenging. In this work, a sustainable cellulose/plant oil based flexible epoxy thermoset with excellent mechanical property, reprocessing performance, and UV absorption property was prepared. First, the amino cellulose is synthesized and used as a reinforcement and curing agent, and then the flexible epoxy thermoset is prepared by curing reaction of amino cellulose, citric acid, and flexible epoxy resin using zinc acetylacetonate as the transesterification catalyst. The epoxy thermosets show excellent thermal stability, the temperature at maximum weight loss reached 425°C. Mechanical property tests indicate that these thermosets have high mechanical strength (19.6 MPa) and satisfactory stretchability (36.1%–118%). The dynamic transesterification ester groups endow the epoxy thermoset with reprocessing ability. In addition, these epoxy thermosets show outstanding and stable UV absorption properties even after long‐time UV‐light irradiation or heating treatment, which makes these flexible epoxy thermosets have promising applications in UV‐blocking coating.
Topiary: Pruning the manual labor from ancestral sequence reconstruction
Authors: Orlandi Kona N. , Phillips Sophia R. , Sailer Zachary R. , Harman Joseph L. , Harms Michael J. 
Published: December 2022

AbstractAncestral sequence reconstruction (ASR) is a powerful tool to study the evolution of proteins and thus gain deep insight into the relationships among protein sequence, structure, and function. A major barrier to its broad use is the complexity of the task: it requires multiple software packages, complex file manipulations, and expert phylogenetic knowledge. Here we introduce topiary, a software pipeline that aims to overcome this barrier. To use topiary, users prepare a spreadsheet with a handful of sequences. Topiary then: (1) Infers the taxonomic scope for the ASR study and finds relevant sequences by BLAST; (2) Does taxonomically informed sequence quality control and redundancy reduction; (3) Constructs a multiple sequence alignment; (4) Generates a maximum‐likelihood gene tree; (5) Reconciles the gene tree to the species tree; (6) Reconstructs ancestral amino acid sequences; and (7) Determines branch supports. The pipeline returns annotated evolutionary trees, spreadsheets with sequences, and graphical summaries of ancestor quality. This is achieved by integrating modern phylogenetics software (Muscle5, RAxML‐NG, GeneRax, and PastML) with online databases (NCBI and the Open Tree of Life). In this paper, we introduce non‐expert readers to the steps required for ASR, describe the specific design choices made in topiary, provide a detailed protocol for users, and then validate the pipeline using datasets from a broad collection of protein families. Topiary is freely available for download: https://github.com/harmslab/topiary.
QuoteTarget: A sequence‐based transformer protein language model to identify potentially druggable protein targets
Authors: Chen Jiaxiao , Gu Zhonghui , Xu Youjun , Deng Minghua , Lai Luhua , Pei Jianfeng 
Published: December 2022

AbstractThe development of efficient computational methods for drug target protein identification can compensate for the high cost of experiments and is therefore of great significance for drug development. However, existing structure‐based drug target protein‐identification algorithms are limited by the insufficient number of proteins with experimentally resolved structures. Moreover, sequence‐based algorithms cannot effectively extract information from protein sequences and thus display insufficient accuracy. Here, we combined the sequence‐based self‐supervised pretraining protein language model ESM1b with a graph convolutional neural network classifier to develop an improved, sequence‐based drug target protein identification method. This complete model, named QuoteTarget, efficiently encodes proteins based on sequence information alone and achieves an accuracy of 95% with the nonredundant drug target and nondrug target datasets constructed for this study. When applied to all proteins from Homo sapiens, QuoteTarget identified 1213 potential undeveloped drug target proteins. We further inferred residue‐binding weights from the well‐trained network using the gradient‐weighted class activation mapping (Grad–Cam) algorithm. Notably, we found that without any binding site information input, significant residues inferred by the model closely match the experimentally confirmed drug molecule‐binding sites. Thus, our work provides a highly effective sequence‐based identifier for drug target proteins, as well to yield new insights into recognizing drug molecule‐binding sites. The entire model is available at https://github.com/Chenjxjx/drug-target-prediction.
Pattern and predictors of medication use among adults in southwestern Nigeria: A community‐based cross‐sectional study
Authors: Adedeji Waheed Adeola , Dairo Magbagbeola David , Nguku Patrick Mboya , Oyemakinde Akin , Fehintola Fatai Adewale 
Published: December 2022

AbstractPopulation‐based drug utilization studies are scanty in Nigeria. The aim was to determine the pattern and predictors of medication use among adults in the communities of Southwestern Nigeria. A cross‐sectional study was conducted among adults selected by multi‐stage sampling from Oyo State communities. The questionnaires, adapted from the WHO Students' Drug Use Questionnaire and previous studies, were pretested and interviewer administered. The respondents' socio‐demographic characteristics, the pattern of medication use, prescribers, and sources of drug acquisition were obtained. Binary logistic regression was used to determine the predictor of medications used. Of the 999 respondents, 501 resided in rural communities while 498 dwelled in urban areas. The mean (±SD) age of the respondents was 38 ± 15 years. The median (range)% prevalence of medication use were as follows: lifetime use, 58.2 (17.7–81.0); current use, 31.2 (8.9–65.9); and past use, 20.3 (9.2–28.9). Medications were mainly obtained from patent medicine stores, median (range%), 71 (65–80). The commonly used drugs were paracetamol, 626 (67.6); nonsteroidal anti‐inflammatory drugs, 174 (18.8); artemether/lumefantrine, 422 (68.2); ampicillin/cloxacillin, 220 (48.6); and chlorpheniramine, 59 (39.9). Factors predictive of current medication use, adjusted odd ratio (95% confidence interval) were as follows: antimalarial [male, 0.7 (0.5, 0.9)]; antibacterial [male, 0.6 (0.4–0.9)]; analgesics [married, 1.5 (1.1–2.2); presence of health facilities, 0.5 (0.3–0.7); and shorter distance to health facility, 1.5 (1.1–2.1)]. Antimalarials, antibacterial, and analgesics were commonly used and inappropriately obtained by adults in Southwestern Nigeria. Factors predictive of current medication use were gender, marital status, the presence of health facilities, and distance to health facilities. There is a need for more extensive countrywide medication use studies and enlightenment programs to ensure the appropriate use of medications.
Using satellite data to assess spatial drivers of bird diversity
Authors: Hunt Merryn L. , Blackburn George Alan , Siriwardena Gavin M. , Carrasco Luis , Rowland Clare S. 
Published: December 2022

AbstractBirds are useful indicators of overall biodiversity, which continues to decline globally, despite targets to reduce its loss. The aim of this paper is to understand the importance of different spatial drivers for modelling bird distributions. Specifically, it assesses the importance of satellite‐derived measures of habitat productivity, heterogeneity and landscape structure for modelling bird diversity across Great Britain. Random forest (RF) regression is used to assess the extent to which a combination of satellite‐derived covariates explain woodland and farmland bird diversity and richness. Feature contribution analysis is then applied to assess the relationships between the response variable and the covariates in the final RF models. We show that much of the variation in farmland and woodland bird distributions is explained (R2 0.64–0.77) using monthly habitat‐specific productivity values and landscape structure (FRAGSTATS) metrics. The analysis highlights important spatial drivers of bird species richness and diversity, including high productivity grassland during spring for farmland birds and woodland patch edge length for woodland birds. The feature contribution provides insight into the form of the relationship between the spatial drivers and bird richness and diversity, including when a particular spatial driver affects bird richness positively or negatively. For example, for woodland bird diversity, the May 80th percentile Normalized Difference Vegetation Index (NDVI) for broadleaved woodland has a strong positive effect on bird richness when NDVI is >0.7 and a strong negative effect below. If relationships such as these are stable over time, they offer a useful analytical tool for understanding and comparing the influence of different spatial drivers.