bluuebunny/crossref_metadata_2025_split huggingface dataset:
A preliminary study on determination of radioactivity levels and estimation of the annual effective dose in dried fruits consumed in Albania
Authors: Spahiu Erjon , Shyti Manjola , Bërdufi Irma 
Published: January 2024

Abstract
This work aimed to support Albania’s food safety monitoring regime. In this context, the natural and artificial radioactivity was measured in 20 samples of dried fruits collected randomly in different markets of Tirana. The activity concentration of 40K, 226Ra, 232Th and 137Cs was determined by using the high-purity germanium detector. The maximum values of activity concentration in dried fruits were calculated as 517 ± 22 Bq kg−1 for 40K, 11.10 ± 0.93 Bq kg−1 for 226Ra, 4.38 ± 0.26 Bq kg−1 for 232Th and 0.83 ± 0.14 Bq kg−1 for 137Cs. The average values of activity concentration of 40K and 226Ra were 269and 6.05 Bq kg−1 and the average effective dose to individuals from the intake of the dried fruits was 44 μSv y−1. All average values in this study were lower than recommended values by reports United Nations Scientific Committee on the Effect of Atomic Radiation, World Health Organization and International Commission on Radiological Protection for all age groups. Therefore, all dried fruit samples in this study are safe for consumption with acceptable radiological risk and none of them pose any significant radiological impact. The obtained data in this paper and information for levels of radioactivity and ingestion absorbed dose from dried fruits can be used to be the basic data for future comparative analysis of the other studies.
Cohort-Specific Experiences of Industrial Decline and Intergenerational Income Mobility
Authors: Seltzer Nathan 
Published: January 2024

Abstract
The United States manufacturing industry has long been regarded as the economic engine that built and sustained the middle class. In recent decades, this pillar of economic opportunity has eroded substantially. Though much has been written about the decline of manufacturing sectors in United States communities, the potential consequences for economic mobility, and stratification processes more generally, remain largely unexplored. In this study, I develop a conceptual framework linking the study of labor market change to economic stratification. I examine how structural changes to United States labor markets have altered opportunities for economic advancement in the United States. I focus the analysis on birth cohorts in the 1980s, whose labor market entry spans the large-scale erosion of the manufacturing industry in the 2000s. I find strong evidence that declines in manufacturing employment have contributed to growing geographic disparities in upward intergenerational income mobility. Children raised in counties that experienced large contractions in manufacturing industries throughout adolescence experienced large economic penalties in adulthood via reduced levels of upward mobility. The results demonstrate how long-term macroeconomic changes can disrupt and redistribute opportunities within societies.
Influence of metabolizable protein and methionine supplementation on growth-performance of Holstein steer calves during the initial 112-d feedlot growing phase
Authors: Salinas-Chavira Jaime , Carvalho Pedro H V , Latack Brooke C , Ferraz Marcos V C , Montano Martin , Zinn Richard A 
Published: January 2024

Abstract
The objective was to examine the effects of metabolizable protein (MP) and ruminal-protected methionine supplementation on growth performance of Holstein steer calves during the initial feedlot growing phase (112 d). One hundred eighty Holstein steer calves (122 ± 7 kg) were blocked by weight and assigned to 30 pens (6 steers per pen). Five treatments were applied: 1) control, a diet based on steam-flaked corn containing urea and dry distillers grains plus solubles as supplemental N sources with no amino acid addition; 2) control diet plus blood meal supplementation; 3) diet from treatment 2, with 0.064% Smartamine M (70% methionine; Adisseo, Alpharetta, GA) supplementation; 4) diet from treatment 2 with 0.096% Smartamine M supplementation; 5) diet from treatment 2 with 0.128% Smartamine M supplementation. All diets were formulated to exceed the estimated MP requirements. The estimated metabolizable lysine, as well as methionine, was deficient in the control diet. Blood meal was added to the control diet to meet estimated lysine requirements (diet 2), the other diets had increasing concentrations of supplemental methionine. Supplemental MP enhanced (10%, P &lt; 0.02) interim and overall 112-d average daily gain (ADG). Additional effects of supplemental methionine on ADG were not appreciable (P &gt; 0.10). Supplemental MP did not affect (P &gt; 0.10) dry matter intake (DMI) during the first 56-d period; however, it tended to increase (P = 0.08) DMI during the subsequent 56-d period. Overall, supplemental MP or methionine had no appreciable effect (P &gt; 0.10) on DMI. Supplemental MP improved (P &lt; 0.01) gain efficiency and estimated dietary net energy (NE) values during the initial 56-d period (11 and 7%, respectively) and overall (7 and 4%, respectively). Supplemental MP did not affect (P &gt; 0.10) gain efficiency during the second 56-d period, although it tended to enhance (P = 0.08) estimated dietary NE. Supplemental methionine did not appreciably affect (P &gt; 0.10) gain efficiency or estimated dietary NE. Therefore, adding MP to cover the estimated limiting amino acid supply in diets may enhance the gain efficiency and dietary energetics of growing Holstein calves. However, amino acid addition supplementation beyond the requirements may not produce extra productive performance of steer calves.
Bayesian Network Modelling for the Clinical Diagnosis of Alzheimer’s Disease
Authors: Bate St Cliere Amber-Rose , Fenton Norman 
Published: January 2024

AbstractAlzheimer’s disease (AD) is a progressively debilitating disease commonly affecting the elderly. Correct diagnosis is important for patients to access suitable therapies and support that can help improve or manage symptoms of the condition. Reports of misdiagnosis and difficulty diagnosing AD highlight existing clinical challenges. Here we propose a Bayesian network as a preliminary model for a complementary clinical diagnostic tool for dementia due to AD and mild cognitive impairment due to AD. The model structure was built based on medical reasoning patterns which help bridge the gap between clinical professionals and algorithmic decision making. The parameters of the model were specified from a combination of learning from data (using the NACC Uniform Data Set), extracting data from literature, and knowledge-based judgment. The resulting model includes variables laid out in NIA-AA diagnostic criteria and differentiates actual AD cases from formal AD diagnoses. The model is validated against a range of real-world data. Unlike machine-learnt (black box) AI models, this model provides a visible and auditable justification for its predictions and can be used for multiple types of ‘what if analysis’. An easy-to-use web accessible version of the model has been made available.
The decline of renal function aggravates arterial stiffness: a large-scale cross-sectional and longitudinal study
Authors: Zhao Qiuping , Wang Wei , Leng Yiming , Wang Jie , Rujia Miao , Chen Zhiheng , Wang Jiangang , Cai Jingjing , Yuan Hong , Li Fei , Lu Yao 
Published: January 2024

ABSTRACTPurposeMany studies investigated the one-single-direction relationship between arterial stiffness and chronic kidney dysfunction, particularly in patients with end-stage renal disease. The bidirectional relevance between kidney function decline and arterial stiffness in general population remains unknown. This study aimed to address the temporary relationship between arterial stiffness and renal function.Materials and MethodsThis large-scale observational study comprised one cross-sectional and one longitudinal population sample totalling 67,060 individuals aged over 18 years with brachial-ankle pulse wave velocity (baPWV) and estimated glomerular filtration rate (eGFR) measurements available. Associations with potential risk conditions were analysed using multiple regression analyses. Cox proportional model was used to investigate the association of arterial stiffness and incident chronic kidney disease (CKD). Cross-lagged path analysis was further conducted to analyze the temporal relationship between baPWV and eGFR.ResultsMultiple regression analyses showed that baPWV was inversely associated with eGFR. Compared with the lower baPWV tertile group, higher baPWV was a predictor of CKD risk, with increased HRs for three baPWV tertile groups [HR=2.17 (1.26-3.76), P for trend <0.05]. Accordingly, lower eGFR was significantly associated with higher arterial stiffness risk, even after full-adjusted [HR=1.21 (1.02-1.44), P for trend <0.05]. In the path analysis, the coefficient of the association between baseline baPWV and follow-up eGFR was lower than the effect of baseline eGFR for follow-up baPWV (−0.063 Vs. −0.077, P <0.001).ConclusionsDecrease of eGFR appeared to aggravate arterial stiffness, which unravelling a new understanding of the role kidney dysfunction played in arterial stiffening.
Measuring progress on health and well-being in the Eastern Mediterranean Region via voluntary national reviews, 2016 - 2021: what does the data reveal?
Authors: Mabry RM , Doctor HV , Khair MN , Abdelgalil M , Rashidian A 
Published: January 2024

AbstractBackgroundCountrysubmission of Voluntary National Reviews (VNRs) is the formal mechanism to report on progress of the Sustainable Development Goals (SDGs). Despite strong political commitment to strong information systems, large data gaps exist in the Eastern Mediterranean Region.MethodsThis study aims to review VNRs submitted by countries in the region to assess the comprehensiveness of reporting on the health-reported SDG targets and indicators. We conducted a content analysis of VNRs of 18 countries of the region submitted between 2016 and 2021. The review focused on progress on the SDGs by assessing i) the reporting on the 50 health-related targets and indicators ii) data availability using the WHO reporting framework, and iii) data availability based on source of information. Spreadsheets were developed and used to extract data and facilitate content analysis.ResultsAll VNRs confirmed that SDG monitoring and reporting mechanisms have been established, however, only 11 VNRs reported on all 17 SDGs and 8 explicitly mentioned country specific 2030 targets. Many VNRs identified data availability as a key challenge to SDG monitoring; for the health SDG, data availability ranged from 48% to 93% among the five countries reporting this figure. Comprehensiveness of reporting varied by type of indicator (maternal, child and infant mortality were the most common) and by country income level (greater reporting by high income countries).ConclusionsSignificant work remains to enhance information systems across the region to monitor progress and guide actions to achieve the health-related SDGs. Strengthening health information systems regulatory frameworks, data collection capacities including strengthening civil registration and vital statistics and population-based surveys are key steps to enhancing access to quality data which in turn can contribute to achieving the health-related SDGs.
Are personal health literacy and school health literacy environment important to schoolteachers’ health outcomes?
Authors: Liu Rongmei , Yu Mingyang , Zhao Qiuping , Wang Junfang , Bai Yuxi , Chen Hui , Yang Xiaomo , Liu Shuaibin , Okan Orkan , Chen Xinghan , Xing Yuhan , Guo Shuaijun 
Published: January 2024

ABSTRACTBackgroundWhile the relationship between an individual’s personal health literacy and health outcomes is well-established, the role of the health literacy environment is often overlooked. This study aimed to examine the associations of personal health literacy and the school health literacy environment with health outcomes among schoolteachers.MethodsA cross-sectional study was conducted in 11 schools in Zhengzhou, Henan, China. Using a self-administered questionnaire, teachers (N=7364) were surveyed collecting data on their sociodemographics, personal health literacy, the school health literacy environment, and four types of health outcomes (health status, health-compromising behaviours, health service use, and healthcare cost). Besides descriptive statistics, a series of logistic regression analyses were conducted.ResultsOverall, more than half of teachers (56.9%) had inadequate or problematic health literacy, while more than three-fifths (69.0%) perceived their school health literacy environment was less supportive. Teachers with inadequate health literacy had higher odds of poor health status (odds ratio (OR)=5.79, 95% CI=3.84, 8.73), at least one health-compromising behaviour (OR=2.90, 95% CI=2.29, 3.68), at least one health service use (OR=2.73, 95% CI=2.07, 3.61), and more healthcare cost (OR=2.51, 95% CI=2.00, 3.16) than those with excellent health literacy, after adjusting for sociodemographics and school health literacy environment. Similarly, teachers who perceived low levels of supportive school health literacy environment had higher odds of poor health outcomes (ORs ranging from 1.13 to 1.78), after adjusting for sociodemographics and personal health literacy.ConclusionBoth personal health literacy and school health literacy environment are important to schoolteachers’ health outcomes. Educational programs and organisational change are needed to improve personal health literacy and school environments to improve teachers’ health and well-being.
MMFP-Tableau: Enabling Precision Mitochondrial Medicine through Integration, Visualization, and Analytics of Clinical and Research Health System Electronic Data
Authors: George-Sankoh Ibrahim , MacMullen Laura E. , Chinwalla Asif T. , Taylor Deanne , Ganetzky Rebecca D. , Stanley Katelynn , McCormick Elizabeth M. , Zolkipli-Cunningham Zarazuela , Falk Marni J 
Published: January 2024

ABSTRACTPurposeTo describe a novel data integration workflow developed to automate clinical and research electronic health system data integration and harmonization from siloed sources for centralized access, visualization and analysis by clinicians and researchers in an end user-friendly customized analytic platform.MethodsA centralized, semi-automated framework provides data provenance and user access to integrated data sources. Data models are implemented leveraging a centralized server (Alteryx) for high-level analytics including scheduling, integration and modeling. A secure Tableau instance hosts end-user visualizations, with minimal software development required.ResultsMMFP-Tableau, named for its origin in the Mitochondrial Medicine Frontier Program (MMFP) at Children’s Hospital of Philadelphia, facilitates direct access to integrated, highly robust health system datasets. This scalable data solution enables integration of clinical and research parameters with research samples; enhances external biopharma collaborations for clinical trial design, subject recruitment and data tracking; accelerates retrospective clinical cohort data analysis; and improves complex data visualization for clinicians and researchers.ConclusionMMFP-Tableau promotes complex data integration, visibility, and advanced analytic capabilities to facilitate seamless multidisciplinary research, benefitting clinical care and research in rare disease patients and cohorts. This approach represents a generalizable workflow concept readily adaptable to implement across diverse fields of medicine
Mindfulness Coaching with Digital Lifestyle Monitoring Enhances Selective Attention in Medical Scientists
Authors: Jaiswal Satish , Nan Jason , Purpura Suzanna R. , Manchanda James K. , Garcia-pak Iris , Ramanathan Dhakshin S. , Chuss Dawna , Rana Deborah T. , Beck Ellen , Insel Paul A. , Chi Neil , Roth David M. , Patel Hemal H. , Mishra Jyoti 
Published: January 2024

AbstractMedical scientists have dual commitments to clinical care and research efforts. Such commitments can create hectic and stressful work schedules, which may impact on well-being and cognition. In this study, we tested the hypothesis that mindfulness coaching plus wearable-based lifestyle monitoring can benefit such individuals. We conducted a waitlist-controlled intervention study (n=43) with M.D./Ph.D. preclinical or graduate students and post M.D./Ph.D. trainees/faculty. Assessments of quantitative outcomes included subjective measures of burnout, mindfulness, self-compassion, and well-being, as well as objective cognitive assessments. The results showed no impacts on subjective measures. However, amongst objective cognitive measures, selective attention performance was significantly improved following the intervention (bias corrected effect size, Hedges’ g = 1.13, p=0.005). Extent of improvement in selective attention correlated with suppression of visual alpha oscillations – a neural marker for distractibility - measured using electroencephalography (EEG) (r=-0.32, p<0.05). Qualitative feedback showed that after receiving the intervention, participants in both groups equally rated the overall experience as “very good” (3.70 ±0.98 out 5). They also appreciated that the intervention emphasized healthy lifestyle behaviors, and contributed to mindfulness, compassion, and a sense of community. A majority (57%) of the participants reported that they expect to change their well-being related behaviors because of the intervention. Overall, this study suggests the utility of mindfulness coaching to improve selective attention skills in medical scientists and that more needs to be done to enhance subjective well-being in such individuals.
Assessing Causal Relationships Between Diabetes Mellitus and Idiopathic Pulmonary Fibrosis
Authors: Moss Samuel , Minelli Cosetta , Leavy Olivia , Allen Richard , Oliver Nick , Wain Louise , Jenkins Gisli , Stewart Iain 
Published: January 2024

AbstractRationaleIdiopathic Pulmonary Fibrosis (IPF) is a disease of progressive lung scarring. There is a known association between IPF and diabetes mellitus (DM), but it is unclear whether this association is due to causal relationships between these traits.ObjectivesTo examine causal relationships between DM, diabetes-associated traits, and IPF using a Mendelian randomisation approach.MethodsFollowing a two-sample Mendelian randomisation (MR) approach, we used genetic variants identified from genome wide association studies (GWAS) for type 1 diabetes (T1D), type 2 diabetes (T2D), glycated haemoglobin level (HbA1c), fasting insulin level, and body mass index (BMI) to assess for evidence of causal effects of these traits on IPF risk. Further analyses using pleiotropy-robust and multivariable MR methods were performed to account for the inherent complexity of the traits being investigated.ResultsResults did not suggest that either T1D (OR = 1.00, 95% CI: 0.93-1.07, p = 0.902) or T2D (OR = 1.02, 95% CI: 0.93-1.11, p = 0.692) are in the causal pathway of IPF. No significant effects were suggested of HbA1c (OR = 1.19, 95% CI: 0.63-2.22, p = 0.592) or fasting insulin level (OR = 0.60, 95% CI: 0.31-1.15, p = 0.124) on IPF risk, but effects of BMI on IPF risk were indicated (OR = 1.44, 95% CI: 1.12-1.85, p = 0.004).ConclusionThis study suggests that DM and IPF are unlikely to be causally linked. This comorbid relationship may instead be driven by shared risk factors or treatment effects.Key messagesWhat is already known on this topic:Idiopathic pulmonary fibrosis is associated with diabetes mellitus epidemiologically, but it is unclear if these traits are linked by causal effects.What this study adds:Idiopathic pulmonary fibrosis and diabetes mellitus are unlikely to be causally linked, suggesting that shared environmental risk factors or treatment effects may drive this comorbid relationship.How this study might affect research, practice, or policy:Further research investigating the relationship between diabetes mellitus and idiopathic pulmonary fibrosis should focus on potential shared risk factors such as smoking, and treatment effects including corticosteroid use.
Automated Classification of At-home SARS-CoV-2 Lateral Flow Assay Test Results using Image Matching and Transfer Learning: multiple-pipeline study
Authors: Safarzadeh Meysam , Herbert Carly , Wong Steven Koon , Stamegna Pamela , Guilarte-Walker Yurima , Wright Colton , Suvarna Thejas , Nowak Chris , Kheterpal Vik , Pandey Shishir , Wang Biqi , Lin Honghuang , O’Connor Laurel , Hafer Nathaniel , Luzuriaga Katherine , Manabe Yuka , Broach John , Zai Adrian H , McManus David D , Du Xian , Soni Apurv 
Published: January 2024

AbstractIntroductionRapid antigen testing for SARS-CoV-2 is an important tool for the timely diagnosis of COVID-19, especially in at-home settings. However, the interpretation of test results can be subjective and prone to error. We describe an automated image analysis pipeline to accurately classify test types and results without human intervention using a dataset of 51,274 rapid antigen test images across three distinct test card brands.MethodsThe proposed method classifies participant-submitted images into four categories: positive for SARS-CoV-2, negative for SARS-CoV-2, invalid/uncertain, and unclassifiable. The model includes four stages: test card classification and region of interest detection using image-matching algorithms, elimination of invalid results using a developed Siamese neural network, and test result classification using transfer learning.ResultsThe model accuracy was very good for test-card classification (100%), region of interest detection (83.5%), and identification of invalid results ranging from 95.6% to 100% for different test types. Performance of the model for test result classification varied by tests; the model’s sensitivity, specificity, and precision for Abbott BinaxNOW™ was 0.761, 0.989, and 0.946, BD Veritor™ At-Home COVID-19 Test was 0.955, 0.993, and 0.877, and for QuickVue® At-Home OTC COVID-19 Test was 0.816, 0.988, and 0.930.ConclusionThe proposed method improved the interpretation of rapid antigen tests, particularly in invalid result detection compared to human-read, and offers a great opportunity for standardization of rapid antigen test interpretation and for providing feedback to participants with invalid tests.
Endometriosis risk is associated with shorter anogenital distance by meta-analysis
Authors: Crespi Bernard J. 
Published: January 2024

AbstractBackgroundAnogenital distance is a well-validated marker of prenatal testosterone, with shorter distances indicating lower levels during early gestation. A suite of studies has linked anogenital distance with risk of endometriosis, but the findings are variable, leading to uncertainty in interpretation. The relationship of anogenital distance with endometriosis is especially important because lower testosterone has been associated with endometriosis in recent Mendelian Randomization studies, which implies causality in the association, with direct implications for future research and treatment.MethodsA systematic review and meta-analysis was conducted on the association of endometriosis with anogenital distance. Three databases were queried in the identification phase, and a random-effects meta-analysis was applied to the data in studies that met the inclusion criteria.ResultsShorter anogenital distance AF, measured from the anus to the posterior fourchette, was significantly associated with higher risk of endometriosis in the meta-analysis. By contrast, there was no such association for anogenital distance AC, measured from the anus to the clitoral surface. Both analyses demonstrated significant heterogeneity across studies. Too few studies were available for robust investigation of publication bias.ConclusionsThe association of short anogenital distance with endometriosis risk provides support for the hypothesis that endometriosis represents, in part, a disorder mediated by relatively low testosterone levels in early prenatal development. This conclusions has notable implications for understanding the causes and treatment of endometriosis.