bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using artificial intelligence in the development of diagnostic models of coronary artery disease with imaging markers: A scoping review
Authors: Wang Xiao , Wang Junfeng , Wang Wenjun , Zhu Mingxiang , Guo Hua , Ding Junyu , Sun Jin , Zhu Di , Duan Yongjie , Chen Xu , Zhang Peifang , Wu Zhenzhou , He Kunlun 
Published: October 2022

BackgroundCoronary artery disease (CAD) is a progressive disease of the blood vessels supplying the heart, which leads to coronary artery stenosis or obstruction and is life-threatening. Early diagnosis of CAD is essential for timely intervention. Imaging tests are widely used in diagnosing CAD, and artificial intelligence (AI) technology is used to shed light on the development of new imaging diagnostic markers.ObjectiveWe aim to investigate and summarize how AI algorithms are used in the development of diagnostic models of CAD with imaging markers.MethodsThis scoping review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline. Eligible articles were searched in PubMed and Embase. Based on the predefined included criteria, articles on coronary heart disease were selected for this scoping review. Data extraction was independently conducted by two reviewers, and a narrative synthesis approach was used in the analysis.ResultsA total of 46 articles were included in the scoping review. The most common types of imaging methods complemented by AI included single-photon emission computed tomography (15/46, 32.6%) and coronary computed tomography angiography (15/46, 32.6%). Deep learning (DL) (41/46, 89.2%) algorithms were used more often than machine learning algorithms (5/46, 10.8%). The models yielded good model performance in terms of accuracy, sensitivity, specificity, and AUC. However, most of the primary studies used a relatively small sample (n &lt; 500) in model development, and only few studies (4/46, 8.7%) carried out external validation of the AI model.ConclusionAs non-invasive diagnostic methods, imaging markers integrated with AI have exhibited considerable potential in the diagnosis of CAD. External validation of model performance and evaluation of clinical use aid in the confirmation of the added value of markers in practice.Systematic review registration[https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022306638], identifier [CRD42022306638].
Natural history and clinical significance of aortic focal intimal flaps
Authors: Maas Austin , van Bakel Pieter A. J. , Ahmed Yunus , Patel Himanshu J. , Burris Nicholas S. 
Published: October 2022

ObjectiveFocal intimal flaps (FIF) are a variety of defects of the aorta that result in a short, flap-like projection into the lumen, and are often encountered in asymptomatic patients undergoing computed tomography angiography (CTA) surveillance for aortic aneurysm, but the natural history and clinical significance of such lesions has not yet been studied.MethodsWe retrospectively identified patients with an asymptomatic FIF and available imaging follow-up (&gt;1 year). FIF was defined as flap-like intimal irregularity &lt; 4 cm in length involving the thoracic aorta (TA), abdominal aorta (AA) or common iliac arteries (CIA). FIF characteristics included length and circumferential extent as well as the presence and size (width and depth) of associated penetrating aortic ulcers (PAUs). Patient characteristics, adverse events and history of surgical repair was determined by chart review. FIFs and associated PAUs were assessed for progression by comparing baseline and follow-up CTA studies.ResultsA total of 84 FIFs were identified in 77 patients. Average age was 69.2 ± 10.1 years, and 81% were male (81%). Common co-morbidities included: hypertension (78%), hyperlipidemia (68%), smoking (60%), coronary artery disease (41%), aortic aneurysm (34%), type II diabetes mellitus (27%) and prior cardiovascular surgery (25%). FIFs were most commonly located in the abdominal aorta (n= 50, 60%). Nearly all FIFs were associated with local atherosclerotic plaque (93%). Mean follow-up interval was 3.5 ± 2.6 years (259 cumulative follow-up years). Change in FIF length and local aortic diameter over follow-up were 0.7 ± 2.3 mm and 0.8 ± 1.1 mm, respectively. Nearly half (47%) of FIFs were associated with penetrating aortic ulcers (PAU) with baseline depth of 7.3 mm (IQR: 6.1–10.2) and change in depth of 0.5 ± 1.4 mm. Only 12% of FIFs and 0% of associated PAUs demonstrated growth (≥3 mm) at follow-up. No acute pathology developed in the location of FIFs and no aortic interventions were performed specifically to treat FIFs.ConclusionFocal intimal flaps identified in asymptomatic patients with aortic disease were co-localized with atherosclerotic plaque and PAUs, and demonstrated indolent behavior, not leading to significant growth or acute aortic events, supporting a conservative management approach.
Secular trends and determinants of influenza vaccination uptake among patients with cardiovascular disease in Korea: Analysis using a nationwide database
Authors: Kim Min , Yang Bumhee , Gu Seonhye , Kim Eung-Gook , Kim So Rae , Oh Kyeong Seok , Yoon Woong-Su , Bae Dae-Hwan , Lee Ju Hee , Kim Sang Min , Choi Woong Gil , Bae Jang-Whan , Hwang Kyung-Kuk , Kim Dong-Woon , Cho Myeong-Chan , Lee Hyun , Lee Dae-In 
Published: October 2022

BackgroundInfluenza vaccination reduces cardiovascular events in patients with cardiovascular disease (CVD). Identifying the factors that affect influenza vaccination uptake can help improve the prognosis in patients with CVD. This study aimed to evaluate the secular trends of influenza vaccination uptake and factors associated with lack of vaccination in individuals with CVD.Materials and methodsWe analyzed the annual trends and factors associated with influenza vaccination among 3,264 patients with CVD, included from the Korea National Health and Nutrition Examination Survey which reflect the health and nutritional status of the nationwide population of Korea conducted between 2007/2008 and 2018/2019. We used a stratified, multistage sampling method.ResultsThe influenza vaccination rate was greater in patients with CVD (53–74%) than in those without CVD (28–40%). Multivariable logistic regression analysis showed that age &lt;50 years [odds ratio (OR), 16.22; 95% confidence interval (CI), 7.72–34.07], 50–64 years (OR, 6.71; 95% CI, 4.37–10.28), male sex (OR, 1.45; 95% CI, 1.14–1.65), and asthma (OR, 0.45; 95% CI, 0.22–0.92) were independently associated with a lack of influenza vaccination. Among patients aged &lt;65 years, smoking (OR, 2.30; 95% CI, 1.31–4.04), college graduation status (OR, 1.81; 95% CI, 1.16–2.82), and hypertension (OR, 0.70; 95% CI, 0.51–0.95) were independently associated with influenza vaccination. For individuals aged 65years, there was no significant determinant of lack of vaccination.ConclusionIn patients with CVD, a continuous increase in the secular trend of influenza vaccination was demonstrated in Korea. Young age, male sex, and non-asthma status were independently associated with lack of influenza vaccination uptake.
Modelled sensitivity of Monte San Lorenzo ice cap, Patagonian Andes, to past and present climate
Authors: Martin Julian , Davies Bethan J. , Jones Richard , Thorndycraft Varyl 
Published: October 2022

Sparse measurements of glacier mass balance, velocity and ice thickness in Patagonia challenge our ability to understand glacier sensitivity to climate change and relate past glacier fluctuations to palaeoclimate change. Small ice caps, such as Monte San Lorenzo, have short response times and high climate sensitivity, making well-dated moraines in their glacier foregrounds an important tool for exploring glacier response to rapid changes in palaeoclimate. Here, the Parallel Ice Sheet Model (PISM) is used to model ice flow across a domain centred on the Monte San Lorenzo ice cap. Ice-flow parameters are calibrated to match present-day ice extent, velocity and thickness. Our aim is, firstly, to quantify present-day physical glacier properties, and ice cap dynamics and sensitivities, and secondarily, to evaluate the controls on the deglaciation of the ice cap within the context of the Southern Hemisphere palaeoclimate system during the Last Glacial-Interglacial Transition (LGIT). The simulated present-day ice cap shows high surface mass flux, with ablation at outlet glacier tongues up to 18 m w. e. a−1, accumulation at the highest elevations of up to 5.5 m w. e. a−1 and a simulated Equilibrium Line Altitude (ELA) of 1750–2000 m asl. The ice cap is more sensitive to changes in precipitation relative to changes in temperature. We provide envelopes with likely ranges of palaeotemperature and palaeoprecipitation for glacial advances to moraines formed during the Last Glacial-Interglacial Transition and Holocene. Our numerical model predicts that cooling and an increase in precipitation is required to force glacial advance to mapped moraine limits at 12.1 ka (2°C cooler, 50% more precipitation), 5.6 ka (0°C cooler, 50% more precipitation) and 0.2 ka (1°C cooler, 25% more precipitation). Our modelling results thus provide insights into the present-day mass balance, thermal regime and velocity of the ice cap, explores the sensitivities of this ice cap to various model and climatic parameters, and provide palaeoclimatic envelopes for readvances during the LGIT and Holocene in Patagonia.
Fatty acid metabolism-related genes in bronchoalveolar lavage fluid unveil prognostic and immune infiltration in idiopathic pulmonary fibrosis
Authors: Lyu Yin , Guo Chen , Zhang Hao 
Published: October 2022

BackgroundIdiopathic pulmonary fibrosis (IPF) is a chronic and progressive condition with an unfavorable prognosis. A recent study has demonstrated that IPF patients exhibit characteristic alterations in the fatty acid metabolism in their lungs, suggesting an association with IPF pathogenesis. Therefore, in this study, we have explored whether the gene signature associated with fatty acid metabolism could be used as a reliable biological marker for predicting the survival of IPF patients.MethodsData on the fatty acid metabolism-related genes (FAMRGs) were extracted from databases like Kyoto Encyclopedia of Genes and Genomes (KEGG), Hallmark, and Reactome pathway. The GSE70866 dataset with information on IPF patients was retrieved from the Gene Expression Omnibus (GEO). Next, the consensus clustering method was used to identify novel molecular subgroups. Gene Set Enrichment Analysis (GSEA) was performed to understand the mechanisms involved. The Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) algorithm was used to evaluate the level of immune cell infiltration in the identified subgroups based on gene expression signatures of immune cells. Finally, the Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate Cox regression analysis were performed to develop a prognostic risk model.ResultsThe gene expression signature associated with fatty acid metabolism was used to create two subgroups with significantly different prognoses. GSEA reveals that immune-related pathways were significantly altered between the two subgroups, and the two subgroups had different metabolic characteristics. High infiltration of immune cells, mainly activated NK cells, monocytes, and activated mast cells, was observed in the subgroup with a poor prognosis. A risk model based on FAMRGs had an excellent ability to predict the prognosis of IPF. The nomogram constructed using the clinical features and the risk model could accurately predict the prognosis of IPF patients.ConclusionThe fatty acid metabolism-related gene expression signature could be used as a potential biological marker for predicting clinical outcomes and the level of infiltration of immune cells. This could eventually enhance the accuracy of the treatment of IPF patients.
Key hepatic signatures of human and mouse nonalcoholic steatohepatitis: A transcriptome–proteome data meta-analysis
Authors: Pyo Jeong Joo , Choi Yongsoo 
Published: October 2022

BackgroundDespite the global prevalence of nonalcoholic fatty liver disease (NAFLD), its pathophysiology remains unclear. In this study, we established highly confident nonalcoholic steatohepatitis (NASH) gene signatures and evaluated the pathological mechanisms underlying NASH through a systematic meta-analysis of transcriptome and proteome datasets obtained from NASH patients and mouse models.MethodsWe analyzed NASH transcriptome datasets from 539 patients and 99 mice. A whole-liver tissue proteome dataset was used to confirm the protein level dysregulation of NASH signatures significant in both humans and mice.ResultsIn total, 254 human and 1,917 mouse NASH gene signatures were established. Up-regulated genes of 254 human signatures were associated with inflammation, steatosis, apoptosis, and extracellular matrix organization, whereas down-regulated genes were associated with response to metal ions and lipid and amino acid metabolism. When different mouse models were compared against humans, models with high fat and high fructose diet most closely resembled the genetic features of human NAFLD. Cross-species analysis revealed 66 genes that were concordantly dysregulated between human and mouse NASH. Among these, 14 genes were further validated to be dysregulated at the protein level. The resulting 14 genes included some of the well-established NASH associated genes and a promising NASH drug target. Functional enrichment analysis revealed that dysregulation of amino acid metabolism was the most significant hepatic perturbation in both human and mouse NASH.ConclusionsWe established the most comprehensive hepatic gene signatures for NASH in humans and mice to date. To the best of our knowledge, this is the first study to collectively analyze the common signatures between human and mouse NASH on a transcriptome–proteome scale.
Spatial distribution and risk identification of arsenic contamination in water and soil through GIS-based interpolation techniques in Jianghan Plain, Central China
Authors: Xiao Tianyun , Muhammad Akhtar Malik , Pan Xiao , Wang Yu , Guangming Hu , Tang Zhonghua 
Published: October 2022

Arsenic is considered a poison because of its seriously toxic effects on the human body; elevated concentrations of arsenic in drinking water have been reported in different parts of the world. Investigating the arsenic distributions in soil, surface water (SW), and groundwater (GW) is an interesting topic of research, along with probing its correlations with local factors of the ecosystem and other hydrogeochemical parameters. This study mainly aims to investigate the impacts of various factors on elevated arsenic concentrations in water and soil. The following factors are assessed for their relationship to the propagation of arsenic in Jianghan Plain, which is the study area: population density, pumping rate, rain, land use, surface elevation, water level, and heavy metal contamination. The arsenic contamination potential prediction map and categories were developed using GIS-based techniques, such as ordinary kriging and quantile methods. Then, the “raster calculator” tool was applied to verify the impacts of the abovementioned factors on arsenic concentration. Eighty-four single-factor, bi-factor, and multi-factor models were established to investigate the effective combinations among the factors. Land use and pumping rate were identified from the soil through an equal frequency tool, whereas water population density and pumping rate were obtained with high matching percentages. The arsenic concentrations varied in the ranges of 0.0001–0.1582 mg/L in GW, 0.0003–0.05926 mg/L in SW, and 1.820–46.620 mg/kg in soil sediment. The single factors showed the best equal frequency of arsenic concentration in water for population density (68.62%) and in soil for land use (65.57%) and pumping (63.66%). Statistical calculations with percentage frequency factors also depicted a positive trend. Arsenic was reported to have high correlations with Fe in GW (r2 = 0.4193), with EC in SW (r2 = 0.4817), and with Cu in soil (r2 = 0.623). It is observed that the alkaline behaviors of water bodies are associated with arsenic mobility. Elevated arsenic values were observed in grids along surface flows with high anthropogenic activities and urbanization. Additionally, low concentrations of Fe depicted reduced activities in aquifer systems. Filtering drinking water as well as controlling the suspected sources and factors affecting concentrations of arsenic in the three phases are options for reducing the health risks of the local populations.
Effect of precipitation on synthetic aperture radar hurricane wind field retrieval
Authors: Guo Chaogang , Ai Weihua , Hu Shensen , Du Xiaoyong , Chen Nan 
Published: October 2022

C-band synthetic aperture radar (SAR) with all-weather observation capability is gradually being used for the high-resolution observation of hurricane. The extreme wind speed in hurricanes is retrieved by combining the co- and cross-polarized SAR signals. However, the heavy precipitation associated with hurricanes will seriously affect the retrieval of SAR sea surface wind speed. In this study, the effects of precipitation-related parameters and phenomena on wind speed retrieval under strong hurricane conditions were examined by using the data from co-located global precipitation measurement Dual-frequency Precipitation Radar, SAR on Sentinel-1 and Radarsat-2, and stepped frequency microwave radiometer. The results show that precipitation will increase the retrieval error of wind speed, and the effect of convective precipitation is more obvious than that of stratiform precipitation. When the wind speed is less than 30 m/s and the rain rate is less than 20 mm/h, the distribution of the melting layer has no obvious effect on SAR wind speed retrieval. Rain cells are mainly the product of convective precipitation and can also be produced when the storm top height is very low. An increase in the vertical-horizontal (VH) polarized normalized radar cross section (NRCS) in rain cells is usually greater than that of the vertical-vertical (VV) polarized NRCS because the sensitivity of the VH signal in a hurricane area is usually greater than that of the VV signal. When the rain rate is low, the difference between the retrieved wind speed inside and outside the rain cells is within the error range of hurricane wind speed retrieval. When the rain rate is further increased, the difference will exceed 10 m/s.
Carbon dioxide fluxes of cyanobacterial crusts and underlying soil under different precipitation patterns in the Ulan Buh Desert, China
Authors: Wang Lili , Gao Ying , Cao Xiaoming , Lu Weiwei 
Published: October 2022

Cyanobacterial crusts, sensitive to changes in the moisture content, are widely distributed in the Ulan Buh Desert. Changes in precipitation patterns due to global climate change are expected to influence the carbon emission and photosynthetic carbon fixation of soil in areas covered with cyanobacterial crusts. We assessed how changes in precipitation amount and frequency affect carbon processes of Cyanobacterial Crusts. Taking average precipitation amount and frequency in August during the past 30 years as control, we established nine precipitation patterns (three amounts × three frequencies). The net carbon flux (NCF) and dark respiration rate (DRR) of cyanobacterial crusts and underlying soil were investigated. Precipitation could stimulate NCF and DRR immediately. With increasing water application times, the peak values of NCF, DRR and 12 h cumulative carbon emissions gradually decreased. Both precipitation amount and frequency significantly affected cumulative carbon emissions but without an interactive effect. Under the same frequency, cumulative carbon emissions increased with increasing precipitation amounts. Under the same total precipitation amount, cumulative carbon emissions caused by high-frequency events were the highest, followed by those of low-frequency precipitation and the control. However, such changes, against the background of a changing global climate, will result in increased carbon emissions of cyanobacterial crusts and underlying Soil, suggesting that cyanobacteria should be considered in projections of the future carbon budget.
Population genomic screening: Ethical considerations to guide age at implementation
Authors: Spencer Scott J. , Fullerton Stephanie M. 
Published: October 2022

Currently, most genetic testing involves next generation sequencing or panel testing, indicating future population-based screening will involve simultaneous testing for multiple disease risks (called here “panel testing”). Genomic screening typically focuses on single or groups of related disorders, with little utilization of panel testing. Furthermore, the optimal age for test ordering is rarely addressed in terms of whether it should coincide with the age of majority (18 years old) or after the age of majority (26 years old). We conducted an ethical analysis utilizing a hypothetical “narrow” panel test comprised of the CDC Tier 1 Genomic Applications: Familial Hypercholesterolemia (FH), increases individuals’ cardiovascular risk due to elevated low-density lipoprotein (LDL) cholesterol levels; Hereditary Breast and Ovarian Cancer (HBOC), increases lifetime risk of developing cancer; and Lynch Syndrome (LS), increases lifetime risk of developing colorectal cancer. We conducted a utilitarian analysis, on the assumption that health systems seek to maximize utility for patients. Screening at the “age of majority” is preferred for FH due to lowering FH patients’ cholesterol levels via statins providing high lifetime benefits and low risks. Screening “after the age of majority” is preferred for HBOC and LS due to availability of effective surveillance, the recommendation for screening activities to begin at age 26, and prophylactic interventions connected to surveillance. We also utilized a supplemental principlist-based approach that identified relevant concerns and trade-offs. Consideration of clinical, non-clinical, and family planning implications suggests narrow panel testing would be best deployed after 26 (rather than at 18) years of age.