bluuebunny/crossref_metadata_2025_split huggingface dataset:
The applicability domain of EPI Suite™ for screening phytotoxins for potential to contaminate source water for drinking
Authors: Rodríguez-Leal Inés , MacLeod Matthew 
Published: September 2022

AbstractBackgroundToxins produced by plants constitute a potential threat to water supplies in Europe, but have not been widely considered in systematic risk assessments. One way to begin to address potential risks of phytotoxins is to conduct screening-level assessments of known phytotoxins for their potential to contaminate source water for drinking due to persistence (P) and mobility (M). Chemical properties relevant for such an assessment (octanol–water partition coefficientKOWand biodegradation half-life) can be estimated from the structure of phytotoxins with quantitative structure–property relationship (QSPR) models found in the United States Environmental Protection Agency’s Estimation Program Interface (EPI Suite™) software, but predictions must be considered critically since these models have been developed using data for anthropogenic chemicals and many phytotoxins could lie outside their applicability domain.ResultsWe analyzed two EPI Suite™models—KOWWIN and BIOWIN5—by evaluating the quality of property predictions for their validation sets as a function of Euclidean distancesdEto the centroid of descriptor space of the models’ training sets. We identified model-specific applicability domain boundaries as local maxima in plots of the difference between root mean square error (∆RMSE) of modeled property values of validation set compounds within and outside applicability domain boundaries defined by a continuum of possible boundaries. And, we also evaluated four generic boundaries that have been suggested in literature. The ∆RMSE between validation set compounds outside and inside applicability domain boundaries had positive values for all but one of the possible boundaries we considered, indicating that properties of chemicals withdEinside the boundaries were better predicted. With our proposed model-specific boundaries, 21% of 1586 phytotoxins produced by plants found in Switzerland were out of domain of KOWWIN, and 46% of were out of domain of BIOWIN5.ConclusionsEstimates of LogKOWand biodegradation half-life of phytotoxins that lie outside the domain of applicability of the QSPR models should be viewed as extrapolations that are subject to unquantified and potentially large errors. Phytotoxins outside the domain of applicability of QSPR models should be prioritized for property measurements as a basis to expand the training sets of QSPR models and to support hazard identification for better management of drinking water quality in Europe.
Genetic analysis of yield traits in Egyptian cotton crosses (Gossypium barbdense L.) under normal conditions
Authors: Abdel-Aty M. S. , Youssef-Soad A , Yehia W. M. B. , EL-Nawsany R. T. E. , Kotb H. M. K. , Ahmed Gamal A. , Hasan Mohamed E. , Salama Ehab A. A. , Lamlom Sobhi F. , Saleh Fouad H. , Shah Adnan Noor , Abdelsalam Nader R. 
Published: September 2022

AbstractTo generate high-yielding cultivars with favorable fiber quality traits, cotton breeders can use information about combining ability and gene activity within a population to locate elite parents and potential F1 crosses. To this end, in the current study, twelve cotton parents (eight genotypes as female parents and four testers) and their F1 crosses obtained utilizing the linex tester mating design were evaluated for their general and specialized combining abilities (GCA and SCA, respectively) of yield traits. The findings showed that for all the investigated variables, variances owing to genotypes, parents, crosses, and parent vs cross showed extremely significant (P ≤ 0.01) differences. Additionally, throughout the course of two growing seasons, the mean squares for genotypes (parents and crosses) showed strong significance for all the variables under study. The greatest and most desired means for all the examined qualities were in the parent G.94, Pima S6, and tester G.86. The best crossings for the qualities examined were G.86 (G.89 × G.86), G.93 × Suvin, and G.86 × Suvin. The parents' Suvin, G89x G86 and TNB were shown to have the most desired general combining ability effects for seed cotton yield/plant, lint yield/plant, boll weight, number of bolls/plants, and lint index, while Suvin, G.96 and pima S6 were preferred for favored lint percentage. For seed cotton yield, lint percentage, boll weight, and number of bolls per plant per year, the cross-G.86 x (G.89 × G.86) displayed highly significant specific combining ability impacts. The crosses G.86 × Suvin, Kar x TNB, G.93 × Suvin, and G.93 × TNB for all the studied traits for each year and their combined were found to have highly significant positive heterotic effects relative to better parent, and they could be used in future cotton breeding programs for improving the studied traits.
Isolated systolic hypertension and its associated risk factors in Iranian middle age and older population: a population-based study
Authors: Hosseinzadeh Ali , Ebrahimi Hossein , Khosravi Ahmad , Emamian Mohammad Hassan , Hashemi Hassan , Fotouhi Akbar 
Published: September 2022

Abstract
Background
Isolated systolic hypertension (ISH), is the most common form of hypertension in older adults. However, the ISH prevalence is not well known in many developing countries such as Iran. This study was conducted to determine the ISH prevalence and its related risk factors in an Iranian population.

Methods
Data were obtained from the second phase of the Shahroud eye cohort study (ShECS) in 2014. ShECS is a longitudinal population-based study which the first phase had been conducted in 2009 using the stratified multistage cluster sampling design on 5190 people aged 40 to 70 years. The ISH prevalence was determined based on the eighth Joint National Commission guidelines for different demographic variables. The associated risk factors were estimated by multiple logistic regression and a two-tailed p-value less than 0.05 was considered significant.

Results
The ISH prevalence was 15.89% (95% CI: 14.88–16.96). It was 15.68% (14.12–17.39) and 15.87% (14.54–17.29) for men and women, respectively. The prevalence of ISH increased significantly with increasing age. The 65–70 compared to 45–69 year age group (OR = 4.21), body mass index (OR = 1.03), diabetes (OR = 1.64), retirement, compared to practitioner job (OR = 1.53), and waist to hip ratio (WHR) (OR = 9.81) were significantly associated with ISH prevalence.

Conclusions
ISH is highly prevalent among the older adult population in Iran. Given the risk of cardiovascular disease associated with ISH, it is recommended to conduct education and public health interventions to improve the detection, prevention, and treatment of ISH.
Binary effects of intravascular laser irradiation of blood on motor recovery and homocysteine reduction in a case with ischemic hemiparesis: portrayed with brain perfusion images
Authors: Li Sheng-Wen A. , Lin Yen-Po , Hsieh Shih-Po , Chang Shin-Tsu 
Published: September 2022

Abstract
Background
Stroke is a burdensome cerebral eventthat affects many aspects of daily activities such as motion, speech, memory, vision, and cognition. Intravascular laser irradiation of blood (ILIB) is a novel therapy, going beyond conventional rehabilitation modalities, that is effective in stroke recovery. Homocysteine ​​is an important risk factor associated with stroke. However, there are few studies that examine the relationship between ILIB treatment and the level of homocysteine. In recent years, researchers use the single-photon emission computed tomography (SPECT) scan of the brain to evaluate stroke patients and patients with a neurologicdeficit. The present report investigates the clinical effect of ILIB treatment on the level of serum homocysteine, the perfusion change of impaired brain region via SPECT, and the patient’s neurologic appearance.

Casepresentation
We focus on a case of a 62-year-old man with subacute stroke accompanied with left hemiparesis and hyperhomocysteinemia, who showed dramatic improvement in muscle power, a decreasing level of homocysteine, and increased blood flow of the right cerebral after three-courseILIB treatment.

Conclusion
We found that ILIB is effective in lowering serum levels of homocysteine and facilitating cerebral circulation for the patient with subacute stroke.
Hungry for more: Australian medical students’ competence, attitudes and preferences towards nutrition education
Authors: Bredhauer Jacqueline , Cone Sam , Brown Lucy , Moseley Genevieve , Wilson Alyce , Perlstein Robyn , Ball Lauren 
Published: September 2022

Abstract
Background
Inadequate nutrition education in medical training is a prevailing global challenge. This study assessed Australian medical students’ self-perceived competencies in nutrition and preferences regarding nutrition education in medical training.

Methods
We conducted a national cross-sectional online survey between September 2019 and January 2020. Our survey collected sociodemographic characteristics and assessed nutrition competency according to a validated assessment tool. All Australian medical students aged over 18 were eligible to participate.

Results
One hundred ninety-five medical students representing 20 Australian medical schools completed the survey and reported moderate nutrition knowledge (17·6 ± 4.1 out of 35, 50%) and skills (29.8 ± 7.6 out of 55, 54%). Students demonstrated positive attitudes towards nutrition training/education (35·9 ± 4.0 out of 40, 90%). Most medical students (n = 148, 72%) reported they had sought some form of nutrition education outside of their degree. Students showed preference for practical, evidence-based nutrition education that is integrated in and prioritised throughout medical training.

Conclusions
Australian medical students express positive attitudes towards nutrition but report only low to moderate nutrition knowledge and skills. There is an opportunity to incorporate practical, regular nutrition learning activities into Australian medical curriculums to equip future doctors to adequately address non-communicable disease. Such initiatives are likely to be well received by students.
Identify diabetic retinopathy-related clinical concepts and their attributes using transformer-based natural language processing methods
Authors: Yu Zehao , Yang Xi , Sweeting Gianna L. , Ma Yinghan , Stolte Skylar E. , Fang Ruogu , Wu Yonghui 
Published: September 2022

Abstract
Background
Diabetic retinopathy (DR) is a leading cause of blindness in American adults. If detected, DR can be treated to prevent further damage causing blindness. There is an increasing interest in developing artificial intelligence (AI) technologies to help detect DR using electronic health records. The lesion-related information documented in fundus image reports is a valuable resource that could help diagnoses of DR in clinical decision support systems. However, most studies for AI-based DR diagnoses are mainly based on medical images; there is limited studies to explore the lesion-related information captured in the free text image reports.

Methods
In this study, we examined two state-of-the-art transformer-based natural language processing (NLP) models, including BERT and RoBERTa, compared them with a recurrent neural network implemented using Long short-term memory (LSTM) to extract DR-related concepts from clinical narratives. We identified four different categories of DR-related clinical concepts including lesions, eye parts, laterality, and severity, developed annotation guidelines, annotated a DR-corpus of 536 image reports, and developed transformer-based NLP models for clinical concept extraction and relation extraction. We also examined the relation extraction under two settings including ‘gold-standard’ setting—where gold-standard concepts were used–and end-to-end setting.

Results
For concept extraction, the BERT model pretrained with the MIMIC III dataset achieve the best performance (0.9503 and 0.9645 for strict/lenient evaluation). For relation extraction, BERT model pretrained using general English text achieved the best strict/lenient F1-score of 0.9316. The end-to-end system, BERT_general_e2e, achieved the best strict/lenient F1-score of 0.8578 and 0.8881, respectively. Another end-to-end system based on the RoBERTa architecture, RoBERTa_general_e2e, also achieved the same performance as BERT_general_e2e in strict scores.

Conclusions
This study demonstrated the efficiency of transformer-based NLP models for clinical concept extraction and relation extraction. Our results show that it’s necessary to pretrain transformer models using clinical text to optimize the performance for clinical concept extraction. Whereas, for relation extraction, transformers pretrained using general English text perform better.
Psychometric properties of the Japanese version of the career competencies questionnaire for nurses: a cross-sectional study
Authors: Yamada Masako , Asakura Kyoko , Takada Nozomu , Hara Yukari , Sugiyama Shoko 
Published: September 2022

Abstract
Background
Career competencies, which are the knowledge, skills, and abilities essential for career development, have been shown to facilitate career success, fulfilling both work and life goals. In dynamically changing healthcare settings, nurses’ career competencies are key for successfully navigating their careers and improving their nursing practice abilities. However, limited studies have examined career competencies in the nursing profession. In particular, no research has been conducted on career competencies among Japanese nurses, which remains a major challenge as voluntary effort is the main factor promoting career and professional development. Therefore, the purpose of this study was to evaluate the validity and reliability of the Japanese version of the Career Competencies Questionnaire (CCQ-J).

Methods
In this cross-sectional study conducted between June 2020 and August 2021, the English CCQ was translated into Japanese using back and forward translation. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted on separate samples. In the first step, item analysis and EFA were conducted with 276 nurses from one hospital. In the second step, CFA was conducted and concurrent validity and reliability were evaluated with 522 nurses from hospitals in the Tohoku region.

Results
Content validity was confirmed by the back-translation report, an expert panel, and a pilot test. The EFA showed that the CCQ-J consisted of a three-factor structure that explained 66.69% of the variance. The CFA revealed that all the fit indices were acceptable [chi-square value (CMIN) = 432.26, degree of freedom (df) = 153, chi-square fit statistic/degree of freedom (CMIN/df) = 2.83, goodness-of-fit index (GFI) = 0.93, adjusted goodness of fit index (AGFI) = 0.89, comparative fix index (CFI) = 0.96, and root mean square error of approximation (RMSEA) = 0.06]. Cronbach’s α for the 21-item CCQ-J and its subscales ranged from 0.85 to 0.95. Concurrent validity was demonstrated via the positive correlation between work engagement, life satisfaction, and the CCQ-J.

Conclusions
The CCQ-J is a valid and reliable instrument to assess the career competencies of Japanese nurses. We hope that the findings presented in this study will contribute to a better understanding of nurses’ career competencies and their successful career and professional development in the future.
Employment status of AFROHUN-Uganda one health alumni, and facilitators and barriers to application of the one health approach: a tracer study
Authors: Ssekamatte Tonny , Mugambe Richard K. , Nalugya Aisha , Isunju John Bosco , Kalibala Patrick , Musewa Angella , Bikaako Winnie , Nattimba Milly , Tigaiza Arnold , Nakalembe Doreen , Osuret Jimmy , Wafula Solomon T. , Okech Samuel , Buregyeya Esther , Tsiouris Fatima , Michaels-Strasser Susan , Kabasa John David , Bazeyo William 
Published: September 2022

Abstract
Background
The One Health (OH) approach integrates multiple competencies in the prevention and control of disease outbreaks. Through a range of OH competence-based activities, the Africa One Health University Network (AFROHUN) built the capacity of selected students at Makerere University and Mbarara University of Science and Technology. This study applied the Systems Theoretical Framework (STF) of career development to establish the employment status of AFROHUN-Uganda alumni, and the facilitators and barriers to application of the OH approach in their organisations.

Methods
We conducted an embedded mixed-methods study among a random sample of 182 AFROHUN-Uganda alumni of the 2013–2018 cohorts. For quantitative data, descriptive statistics were computed using Stata 14.0 statistical software. A total of 12 in-depth interviews were conducted, and NVivo 12 Pro was used to organise data during thematic analysis.

Results
While the majority, 87.4% were or got employed after participating in the AFROHUN Uganda capacity building programme, 68.1% were employed at the time of the survey, 57.7% had worked with their current employer for at least a year, and 39% held managerial positions. The facilitators of applying the OH approach into employing organisations included being knowledgeable about OH, the presence of a multidisciplinary workforce, the nature of activities implemented, and existing partnerships and collaborations between organisations. The barriers to the application of the OH approach included limited funding, a negative attitude towards working with people from other disciplines, and limited knowledge of the One Health approach.

Conclusion
Notably, more than two-thirds of the OH alumni were employed, and more than a third held managerial position. While these findings portray a fairly good absorption rate of the OH alumni into the workforce, they also highlight the facilitators of application of the OH approach that need to be promoted as well as the barriers that need to be addressed if the application of the OH approach is to be improved within the workforce.
Developing the minimum data set of the corrosive ingestion registry system in Iran
Authors: Mahmoudvand Zahra , Shanbehzadeh Mostafa , Shafiee Mohsen , Kazemi-Arpanahi Hadi 
Published: September 2022

Abstract
Background
Corrosive ingestion is still a major health problem, and its outcomes are often unpredicted. The implementation of a registry system for poisoning with corrosive substances may improve the quality of patient care and might be useful to manage this type of poisoning and its complications. Therefore, our study aimed to establish a minimum data set (MDS) for corrosive ingestion.

Methods
This was an applied study performed in 2022. First, a literature review was conducted to identify the potential data items to be included in the corrosive ingestion MDS. Then, a two-round Delphi survey was performed to attain an agreement among experts regarding the MDS content, and an additional Delphi step was used for confirming the final MDS by calculating the individual item content validity index (CVI) and content validity ratio (CVR) and by using other statistical tests.

Results
After the literature review, 285 data items were collected and sent to a two-round Delphi survey in the form of a questionnaire. In total, 75 experts participated in the Delphi stage, CVI, kappa, and CVR calculation. Finally, the MDS of the corrosive ingestion registry system was identified in two administrative and clinical sections with 21 and 152 data items, respectively.

Conclusions
The development of an MDS, as the first and most important step towards developing the corrosive ingestion registry, can become a standard basis for data collection, reporting, and analysis of corrosive ingestion. We hope this MDS will facilitate epidemiological surveys and assist policymakers by providing higher quality data capture to guide clinical practice and improve patient-centered outcomes.
Circulating serum metabolites as predictors of dementia: a machine learning approach in a 21-year follow-up of the Whitehall II cohort study
Authors: Machado-Fragua Marcos D. , Landré Benjamin , Chen Mathilde , Fayosse Aurore , Dugravot Aline , Kivimaki Mika , Sabia Séverine , Singh-Manoux Archana 
Published: September 2022

Abstract
Background
Age is the strongest risk factor for dementia and there is considerable interest in identifying scalable, blood-based biomarkers in predicting dementia. We examined the role of midlife serum metabolites using a machine learning approach and determined whether the selected metabolites improved prediction accuracy beyond the effect of age.

Methods
Five thousand three hundred seventy-four participants from the Whitehall II study, mean age 55.8 (standard deviation (SD) 6.0) years in 1997–1999 when 233 metabolites were quantified using nuclear magnetic resonance metabolomics. Participants were followed for a median 21.0 (IQR 20.4, 21.7) years for clinically-diagnosed dementia (N=329). Elastic net penalized Cox regression with 100 repetitions of nested cross-validation was used to select models that improved prediction accuracy for incident dementia compared to an age-only model. Risk scores reflecting the frequency with which predictors appeared in the selected models were constructed, and their predictive accuracy was examined using Royston’s R2, Akaike’s information criterion, sensitivity, specificity, C-statistic and calibration.

Results
Sixteen of the 100 models had a better c-statistic compared to an age-only model and 15 metabolites were selected at least once in all 16 models with glucose present in all models. Five risk scores, reflecting the frequency of selection of metabolites, and a 1-SD increment in all five risk scores was associated with higher dementia risk (HR between 3.13 and 3.26). Three of these, constituted of 4, 5 and 15 metabolites, had better prediction accuracy (c-statistic from 0.788 to 0.796) compared to an age-only model (c-statistic 0.780), all p<0.05.

Conclusions
Although there was robust evidence for the role of glucose in dementia, metabolites measured in midlife made only a modest contribution to dementia prediction once age was taken into account.