bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-data settlement prediction along a road section integrating InSAR and coastal subsurface information with data assimilation
Authors: Verberne Manon , Koster Kay , Fokker Peter A. 
Published: January 2024

This paper presents a novel approach to examining the impact of soil settlement and its spatial distribution on infrastructure. The study focuses on a specific road section in the Friesland coastal plain in the north of the Netherlands, investigating how the Holocene coastal subsurface architecture influences settlement patterns. Our study underscores the importance of integrating multiple datasets, providing data at varying resolutions. The road segment traverses lithostratigraphical units, which include tidal channel and tidal flat deposits, overlaying an older tidal basin system and intercalated peat beds. Through data assimilation of a settlement model optimized with InSAR measurements, we have identified settlement heterogeneities that can be explained by combining high-resolution variations in lithology with gradual changes in lithostratigraphy. This was accomplished by utilizing a medium-resolution model (MRM) based on borehole descriptions and a high-resolution data (HRD) approach based on cone penetration tests along the road. The HRD method proved more effective in capturing abrupt changes in lithology between channel structures, while the MRM provided a continuous representation of the lithostratigraphic setting of the area. Our study demonstrates that subsurface heterogeneities have significant implications for subsidence along roads. Settlement rates increase from 2–4 mm/year towards 9 mm/year along the road section, resulting in a differential settlement of more than 5 mm/year over a distance of less than a kilometer. This is primarily attributed to variations in lithostratigraphy. Overall, this new innovative approach offers a practical and cost-effective solution for predicting subsidence due to settlement, eliminating the need for expensive laboratory tests. By integrating lithology and lithostratigraphy, more efficient road maintenance and management become possible.
Flood mapping of the lower Mejerda Valley (Tunisia) using Sentinel-1 SAR: geological and geomorphological controls on flood hazard
Authors: Khemiri Lamia , Katlane Rim , Khelil Mannoubi , Gaidi Seifeddine , Ghanmi Mohamed , Zargouni Fouad 
Published: January 2024

Understanding the influence of the hydrological regime changes, encompassing both the duration and spatial extent of floods, is explored, through this paper, in the context of the complex interactions of the geological, geomorphological and climate change conditions. Integrating these parameters and their combined influence becomes paramount for effective flood risk management and disaster prevention, as highlighted in the broader context of the study’s conclusions. Over the past decade, despite prevailing drought conditions in North African countries, the Mejerda Valley in Tunisia has experienced several major flood events. The valley geomorphological history is presented, within the landscape evolution. This study explores the use of Sentinel-1 radar data for detecting and managing floods in the region, with a particular emphasis on the vulnerability of the Lower Mejerda Valley. Sentinel-1 radar data, owing to their continuous monitoring capabilities independent of weather conditions, prove highly effective in tracking the temporal evolution of floods and accurately mapping the extent of affected areas. The methodology utilized in this study has proven to be highly effective in accurately identifying areas susceptible to flooding, both spatially and temporally. In generating classified flood images, water objects are highlighted by applying a specific formula. The study delves into significant flood events in the Mejerda Valley, including occurrences in 2015, 2017, 2019, and 2020, examining their profound impacts on various regions. For instance, the floods of 2015 recorded precipitation levels reaching up to 141 mm, contributing to the overall understanding of flood evolution in the region. In conclusion, the Mejerda Delta’s relief is primarily due to tectonism, influencing both Mio-Pliocene and Quaternary processes, shaping the current delta configuration. The Valley’s topography results from extensive geomorphological evolution, with the eastward shoreline advance leading to the formation of sebkhas and lagoons, indicators of high flood risk, supported by detailed flood event analysis. Moreover, The climate change and anthropic activity are non-negligible parameters influencing flood occurrence and intensity.
Dropout in Andalusian universities: prediction and prevention
Authors: Fernández Cruz Manuel , Álvarez Ferrándiz Daniel , Fernández García-Valdecasas F. Borja , González Castellón Esther 
Published: January 2024

Problem and objectiveUniversity dropout is a major problem that affects more than 31,000 students each year in Andalusian universities, with serious personal and social consequences and an economic cost of more than 222 million euros for the region’s public administration. As concluded from the review of explanatory models we reviewed, dropout has a multicausal origin. The purpose of our work is to test the efficacy of the use of a screening for the early detection of the risk of academic dropout in Higher Education in Andalusian universities.ProcedureWe applied a screening instrument adapted for incoming students in public universities in Andalusia. The survey was applied at the beginning of the second semester. In this article we present data from a sample composed of 976 subjects from the universities of Granada UGR, Jaén UJA and Pablo de Olavide de Sevilla UPO.ResultsWith the data obtained we have established the dropout risk group, which includes those students who do not reach an average score of 3.00 in the total screening. There are 34 students representing 3.48% of the sample. Of these 34 students, 26 are women and 8 are men; 20 belong to the UGR, 8 to the UJA and 5 to the UPO. The detection of the risk group will allow the universities to apply preventive measures in a personalized and adjusted way to avoid possible dropout.
Risk factors of cerebrospinal fluid leakage after neuroendoscopic transsphenoidal pituitary adenoma resection: a systematic review and meta-analysis
Authors: Zhao Jiahui , Wang Shisong , Zhao Xudong , Cui Haohao , Zou Cunyi 
Published: January 2024

IntroductionCerebro spinal fluid (CSF) leakage is common and might lead to severe postoperative complications after endoscopic transsphenoidal pituitary adenoma resection. However, the risk factors of postoperative CSF leakage are still controversial. This article presents a systematic review to explore the explicit risk factors of CSF leakage after endoscopic transsphenoidal pituitary adenomere section.MethodsPRISMA and AMSTAR guidelines were followed to assess the methodological quality of the systematic review. PubMed, Medline, Embase, Web of Science, Cochrane, Clinical Trails, CNKI, CBM, Wan Fang, and VIP databases were searched for all studies on postoperative CSF leak risk factors. The quality of the included studies was assessed by the Newcastle-Ottawa scale. Review Manager 5.4 software was used to calculate the pooled effect size of potential factors with statistical significance.ResultsA total of 6775 patients with pituitary adenoma across 18 articles were included, containing 482 cases of postoperative CSF leakage (accounting for 7.11%). All of the articles had a quality score &gt; 5, indicating good quality. Meta-analysis showed that an increased risk of CSF leak was found for higher levels of BMI (MD=1.91, 95% CI (0.86,2.96), bigger tumor size [OR=4.93, 95% CI (1.41,17.26)], greater tumor invasion (OR=3.01, 95% CI (1.71, 5.31), the harder texture of tumor [OR=2.65, 95% CI (1.95,3.62)], intraoperative cerebrospinal fluid leakage [OR=5.61, 95% CI (3.53,8.90)], multiple operations [OR=2.27, 95% CI (1.60,3.23)].ConclusionBMI, multiple operations, tumor size, tumor invasion, hard texture, and intraoperative cerebrospinal fluid leakage are the risk factors of postoperative CSF leakage. Clinical doctors should pay attention to these risk factors, and conduct strict skull base reconstruction and careful postoperative management.
Assessment of potential risk factors associated with gestational diabetes mellitus: evidence from a Mendelian randomization study
Authors: Fu Qingming , Chen Rumeng , Xu Shuling , Ding Yining , Huang Chunxia , He Binsheng , Jiang Ting , Zeng Bin , Bao Meihua , Li Sen 
Published: January 2024

BackgroundPrevious research on the association between risk factors and gestational diabetes mellitus (GDM) primarily comprises observational studies with inconclusive results. The objective of this study is to investigate the causal relationship between 108 traits and GDM by employing a two-sample Mendelian randomization (MR) analysis to identify potential risk factors of GDM.MethodsWe conducted MR analyses to explore the relationships between traits and GDM. The genome-wide association studies (GWAS) for traits were primarily based on data from the UK Biobank (UKBB), while the GWAS for GDM utilized data from FinnGen. We employed a false discovery rate (FDR) of 5% to account for multiple comparisons.ResultsThe inverse-variance weighted (IVW) method indicated that the genetically predicted 24 risk factors were significantly associated with GDM, such as “Forced expiratory volume in 1-second (FEV1)” (OR=0.76; 95% CI: 0.63, 0.92), “Forced vital capacity (FVC)” (OR=0.74; 95% CI: 0.64, 0.87), “Usual walking pace” (OR=0.19; 95% CI: 0.09, 0.39), “Sex hormone-binding globulin (SHBG)” (OR=0.86; 95% CI: 0.78, 0.94). The sensitivity analyses with MR-Egger and weighted median methods indicated consistent results for most of the trats.ConclusionOur study has uncovered a significant causal relationship between 24 risk factors and GDM. These results offer a new theoretical foundation for preventing or mitigating the risks associated with GDM.
A combined analysis of TyG index, SII index, and SIRI index: positive association with CHD risk and coronary atherosclerosis severity in patients with NAFLD
Authors: Dong Wenyuan , Gong Yuxin , Zhao Jianqi , Wang Yanan , Li Bao , Yang Youdong 
Published: January 2024

BackgroundInsulin resistance(IR) and inflammation have been regarded as common potential mechanisms in coronary heart disease (CHD) and non-alcoholic fatty liver disease (NAFLD). Triglyceride-glucose (TyG) index is a novel biomarker of insulin resistance, System immune-inflammation index(SII) and Systemic inflammation response index(SIRI) are novel biomarkers of inflammation, these biomarkers have not been studied in CHD with NAFLD patients. This study investigated the correlation between the TyG index, SII index, and SIRI index and CHD risk among NAFLD patients.MethodsThis cross-sectional study included 407 patients with NAFLD in the Department of Cardiology, The Second Hospital of Shanxi Medical University. Of these, 250 patients with CHD were enrolled in the NAFLD+CHD group and 157 patients without CHD were enrolled as NAFLD control. To balance covariates between groups, 144 patients were selected from each group in a 1:1 ratio based on propensity score matching (PSM). Potential influences were screened using Lasso regression analysis. Univariate and multivariate logistic regression analyses and the Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to assess independent risk and protective factors for CHD. Construction of nomogram using independent risk factors screened by machine learning. The receiver operating characteristic(ROC) curve was used to assess the ability of these independent risk factors to predict coronary heart disease. The relationship between the Gensini score and independent risk factors was reflected using the Sankey diagram.ResultsThe LASSO logistic regression analysis and Logistic regression analyses suggest that TyG index (OR, 2.193; 95% CI, 1.242-3.873; P = 0.007), SII index (OR, 1.002; 95% CI, 1.001-29 1.003; P &lt;0.001), and SIRI index (OR,1.483;95%CI,1.058-2.079,P=0.022) are independent risk factors for CHD. At the same time, Neutrophils, TG, and LDL-C were also found to be independent risk factors in patients, HDL-C was a protective factor for CHD in patients with NAFLD. Further analysis using three machine learning algorithms found these independent risk factors to have good predictive value for disease diagnosis, SII index shows the highest predictive value. ROC curve analysis demonstrated that combining the SII index, SIRI index, and TyG index can improve the diagnostic ability of non-alcoholic liver cirrhosis patients with CHD.ROC curve analysis showed that the combined analysis of these independent risk factors improved the predictive value of CHD(AUC: 0.751; 95% CI: 0.704-0.798; P &lt;0.001).ConclusionTyG index, SII index, and SIRI index are all independent risk factors for CHD in patients with NAFLD and are strongly associated with prediction and the severity of CHD.
Thyroid function and thyroid homeostasis parameters are associated with increased urinary albumin excretion in euthyroid individuals over 60 years old from NHANES
Authors: Liu Xue , Li Yuchen , Chai Yuwei , Zhang Yuhao , Zhang Li , Zhang Haiqing 
Published: January 2024

IntroductionThe relationship between thyroid function/homeostasis parameters and renal function has been extensively studied. However, the relationship between thyroid function and thyroid homeostasis parameters with albuminuria among elderly individuals remains unclear.MethodsThe population was divided into an albuminuria group and a non-albuminuria group for baseline characteristic difference analysis. Multivariable logistic regression was used to test the association between thyroid function, and thyroid homeostasis parameters and albuminuria. The nonlinear relationship was explored with restricted cubic splines. Meanwhile, we investigated whether the relationship also existed in the diabetes and hypertension subgroups. Receiver operating characteristic (ROC) curves were used to assess the effectiveness of the indices.ResultsFT4 and TFQIFT4 were positively correlated with albuminuria (OR = 1.12; 95% CI = 1.02–1.23, p = 0.02; OR = 1.79; 95% CI = 1.08–2.99, p = 0.03), and FT3/FT4 was negatively correlated with albuminuria (OR = 0.03; 95% CI = 0.00–0.26, p = 0.003). Additionally, the nonlinear relationship between FT3/FT4 as well as TSHI and albuminuria was approximately U-shaped. Similar results were observed in the hypertension subgroup but not in the diabetes subgroup. There was a U-shaped nonlinear relationship between FT3 and albuminuria in the diabetes group. In addition, FT3/FT4 performed better than TFQI, TT4RI, and TSHI in ROC analyses for albuminuria prediction.ConclusionFT4, TFQIFT4, and a low FT3/FT4 ratio were risk factors for albuminuria in euthyroid individuals over 60 years old. However, FT3 was more associated with albuminuria in the diabetes subgroup. TSH was not associated with albuminuria in any analysis. In our study, we attempted to provide more reasonable thyroid parameters and basis for evaluating patients with underlying albuminuria. FT3/FT4 may be used as a helpful indicator to predict albuminuria and provide novel ideas for the evaluation and treatment of albuminuria.
Predicted visceral adiposity index in relation to risk of coronary heart disease and all-cause mortality: insights from NHANES
Authors: Luo Yixing , Zhan Xiangpeng , Liu Yang , Chen Luyao , Zhu Liang , Cai Wenyao 
Published: January 2024

Background and aimsThe Visceral Adiposity Index (VAI) is a straightforward and gender-specific marker that combines anthropometric measurements with lipid profiles. The objective of this study was to evaluate the relationship between VAI and coronary heart disease (CHD).Methods and resultsThe study examined data collected from adults during the NHANES 1999-2018 cycle. The analyses were weighted, and multivariable logistic regression models were employed to investigate the association between VAI and CHD. Additionally, subgroup analyses stratified by age were conducted. To evaluate the impact of VAI levels on survival outcomes, the study utilized the Kaplan-Meier method and performed the log-rank test to evaluate the survival outcome of participants with different VAI levels. The study findings revealed a significant association between VAI and CHD, indicating a non-linear relationship where an increase in VAI was associated with an elevated risk of CHD. High levels of VAI were linked to an increased prevalence of CHD (Q4 vs Q1, OR 1.50, 95% CI 1.12-2.01, P=0.01). Additionally, higher levels of VAI were associated with a poorer overall prognosis in terms of survival outcomes. There were no statistically significant differences in survival outcomes among the population with CHD.ConclusionThe results of this study highlighted a significant association between VAI and CHD, with a non-linear relationship observed. High VAI levels were associated with an increased risk of CHD and poor survival outcomes, emphasizing the importance of understanding and managing this risk factor, particularly in older age groups.
Controversial causal association between IGF family members and osteoporosis: a Mendelian randomization study between UK and FinnGen biobanks
Authors: Tang Jie , Zhao Chanjuan , Lin Sha , Li Xing , Zhu Binlu , Li Yifei 
Published: January 2024

ObjectivesOsteoporosis, a prevalent skeletal disorder characterized by reduced bone strength, is closely linked to the IGF system, crucial for skeletal metabolism. However, the precise nature of this relationship remains elusive. In this study, we employed Mendelian randomization (MR) to unravel the associations between genetically predicted serum IGF system member levels and osteoporosis.MethodsA two-sample MR approach was employed to investigate these causal associations based on two individual datasets. Predictions of 14 serum levels of IGF system members were made using 11,036,163 relevant Single Nucleotide Polymorphisms (SNPs) within a cohort of 4,301 individuals of European descent. Genetic association estimates for osteoporosis were derived from two publicly available GWAS consortia: the Finnish consortium from the FinnGen biobank, comprising 212,778 individuals of Finnish descent (3,203 cases and 209,575 controls), and the UK consortium from the UK Biobank, including 337,159 individuals of European descent (5,266 cases and 331,893 controls).ResultsAccording to the UK dataset, IGF-1 levels were associated with a reduced risk of osteoporosis, as indicated by the weighted median method (Odds Ratio [OR] = 0.998, 95% CI = 0.997–1.000, P = 0.032). Additionally, higher levels of IGFBP-3 were linked to a decreased risk of osteoporosis using the Inverse-Variance Weighted (IVW) method (OR = 0.999, 95% CI = 0.998–1.000, P = 0.019), and CTGF levels exhibited a negative association with osteoporosis, as determined by the weighted median method (OR = 0.998, 95% CI = 0.996–0.999, P = 0.004). In the FinnGen dataset, IGF-1 and IGFBP-3 were not identified to be associated with osteoporosis. While, IGF-LR1 levels displayed a negative association with osteoporosis, according to the MR-Egger method (OR = 0.886, 95% CI = 0.795–0.987, P = 0.036), while CYR61 was linked to an increased risk of osteoporosis based on both the weighted median and IVW methods (OR = 1.154, 95% CI = 1.009–1.319, P = 0.037, and OR = 1.115, 95% CI = 1.022–1.215, P = 0.014, respectively).ConclusionThis study provides compelling evidence that certain IGF family members play a role in the pathogenesis of osteoporosis between different datasets, indicating population specific causal effects between IGF family and osteoporosis. Although the results from both datasets demonstrated that IGF family involved in the pathogenesis of osteoporosis, but the responding key molecules might be various among different population. Subsequent research is warranted to evaluate the potential of these biomarkers as targets for osteoporosis prevention and treatment in specific population.
Factors driving carbon accumulation in forest biomass and soil organic carbon across natural forests and planted forests in China
Authors: Wang Tao , Dong Lingbo , Liu Zhaogang 
Published: January 2024

IntroductionForests play a pivotal role within the global carbon cycle. However, how to enhance carbon storage in existing forests remains unclear.MethodsIn this study, we conduct a comprehensive analysis of data from 2,948 forest sites across China. Utilizing structural equation modeling (SEM), we investigate the intricate relationship between climate, tree species diversity, stand structure, function traits, initial biomass carbon stocks (BCi), soil organic carbon stocks (Soil C content), and carbon accumulation in biomass (ΔBC) and soil organic carbon stocks (ΔSOC) within both natural forests (NF, n = 1,910) and planted forests (PF, n = 1,038).ResultsOur findings underscore the critical influence of tree species diversity and stand structure drivers of both direct and indirect carbon accumulation, with distinct drivers emerging based on the carbon pools in NF and PF. Specifically, increasing tree species diversity from its minimum to maximum value through management-results in a 14.798 tC/ha reduction in BC and 0.686 tC/ha in SOC in NF. Conversely, amplifies BC and SOC in PF by 0.338 tC/ha and 0.065 tC/ha, respectively. Enhancing stand structure-such as stand density-results in a 231.727 tC/ha reduction in BC and SOC in NF, and a 10.668 tC/ha in BC and 64.008 tC/ha increment in SOC in PF.DiscussionOverall, our results indicate that higher tree species diversity, stand density and age-group limits further carbon accumulation in BC and SOC in current NF. In contrast, low tree species diversity and stand density limits the development of carbon storage potential in planted forests. To enhance carbon sequestration capacity, China should change its current policy of completely banning logging of natural forests. Natural forests need thinning and reduced tree species diversity, while planted forests should increase tree species diversity and stand density.