bluuebunny/crossref_metadata_2025_split huggingface dataset:
MAFLD and NAFLD in the prediction of incident chronic kidney disease
Authors: Kwon So Yoon , Park Jiyun , Park So Hee , Lee You-Bin , Kim Gyuri , Hur Kyu Yeon , Koh Janghyun , Jee Jae Hwan , Kim Jae Hyeon , Kang Mira , Jin Sang-Man 
Published: January 2023

AbstractWhether metabolic dysfunction-associated fatty liver disease (MAFLD) can replace nonalcoholic fatty liver disease (NAFLD) is under debate. This study evaluated which definition better predicted incident chronic kidney disease (CKD). This was a 5.3-year (range, 2.8–8.3) retrospective cohort study of 21,713 adults who underwent at least two serial health examinations. Cox analyses were used to compare the risk of incident CKD among non-fatty liver disease (FLD) without metabolic dysregulation (MD; reference), non-FLD with MD, MAFLD-only, NAFLD-only, or both-FLD groups. Non-FLD with MD group (hazard ratio [HR] 1.23, 95% confidence interval [CI] 1.00–1.53), both-FLD group (HR 1.50, 95% CI 1.19–1.89), and MAFLD-only group (HR 1.97, 95% CI 1.49–2.60), but not NAFLD-only group (HR 1.06, 95% CI 0.63–1.79) demonstrated an increased risk of CKD. The increased risk of CKD was significant in MAFLD subgroups with overweight/obesity (HR 2.94, 95% CI 1.91–4.55), diabetes (HR 2.20, 95% CI 1.67–2.90), MD only (HR 1.50, 95% CI 1.19–1.89), excessive alcohol consumption (HR 2.71, 95% CI 2.11–3.47), and viral hepatitis (HR 2.38, 95% CI 1.48–3.84). The switch from NAFLD to MAFLD criteria may identify a greater number of individuals at CKD risk. The association was also significant in MAFLD patients with excessive alcohol consumption or viral hepatitis.
Fractal algorithms and RGB image processing in scribal and ink identification on an 1819 secret initiation manuscript to the “Philike Hetaereia”
Authors: Andronache Ion , Liritzis Ioannis , Jelinek Herbert F. 
Published: January 2023

AbstractHistorical texts incorporate important characteristics that need to be assessed including genre, text structure and content. Often overlooked are characteristics of handwritten manuscripts commonly divided into legibility, readability and aesthetics. To determine the scientific feasibility of classification of handwritten texts an objective approach is developed to describe twenty handwritten pages of an 1819 Greek manuscript, that refers to the initiation to the Greek secret “friendly society” (Philike Hetaereia) organization, established as part of the Greek independence against the Ottoman Turks. It is investigated through a fractal and RGB image analysis approach. Fractal Minkowski Dimension was applied on the handwritten text and the RGB color analysis on the ink and paper and both were used as a non-invasive manner and revealed interesting results. The novel RGB image analysis and the fractal analysis of the manuscript identified respectively, five iron gall inks and four scribes from the ink content and handwritten styles, of the compact five lines text and whole text pages. The novel approach was verified with another old manuscript of known ink pigments, as well as with thirteen known handwritten texts of that period and four prints representing modern and similar period texts substantiating the findings of the novel methods.
Behavioral and cognitive performance of humanized APOEε3/ε3 liver mice in relation to plasma apolipoprotein E levels
Authors: Kessler Kat , Giannisis Andreas , Bial Greg , Foquet Lander , Nielsen Henrietta M. , Raber Jacob 
Published: January 2023

AbstractPlasma apolipoprotein E levels were previously associated with the risk of developing Alzheimer’s disease (AD), levels of cerebrospinal fluid AD biomarkers, cognition and imaging brain measures. Outside the brain, the liver is the primary source of apoE and liver transplantation studies have demonstrated that liver-derived apoE does not cross the blood–brain-barrier. How hepatic apoE may be implicated in behavioral and cognitive performance is not clear. In the current study, we behaviorally tested FRGN mice with humanized liver harboring the ε3/ε3 genotype (E3-human liver (HL)) and compared their behavioral and cognitive performance with that of age-matched ε3/ε3 targeted replacement (E3-TR) mice, the latter produces human apoE3 throughout the body whereas the E3-HL mice endogenously produce human apoE3 only in the liver. We also compared the liver weights and plasma apoE levels, and assessed whether plasma apoE levels were correlated with behavioral or cognitive measures in both models. E3-HL were more active but performed cognitively worse than E3-TR mice. E3-HL mice moved more in the open field containing objects, showed higher activity levels in the Y maze, showed higher activity levels during the baseline period in the fear conditioning test than E3-TR mice, and swam faster than E3-TR mice during training to locate the visible platform in the water maze. However, E3-HL mice showed reduced spatial memory retention in the water maze and reduced fear learning and contextual and cued fear memory than E3-TR mice. Liver weights were greater in E3-HL than E3-TR mice and sex-dependent only in the latter model. Plasma apoE3 levels were similar to those found in humans and comparable in female and male E3-TR mice but higher in female E3-HL mice. Finally, we found correlations between plasma apoE levels and behavioral and cognitive measures which were predominantly model-dependent. Our study demonstrates mouse-model dependent associations between plasma apoE levels, behavior and cognition in an ‘AD-neutral’ setting and suggests that a humanized liver might be sufficient to induce mouse behavioral and cognitive phenotypes.
A multistage model for rapid identification of geological features in shield tunnelling
Authors: Hu Min , Lu Jing , Zhou WenBo , Xu Wei , Wu ZhaoYu 
Published: January 2023

AbstractDecision-making on shield construction parameters depends on timely and accurate geological condition feedback. Real-time mastering of geological condition around the shield during tunnelling is necessary to achieve safe and efficient construction. This paper proposes a Rapidly Geological Features Identification (RGFI) method that balances the model's generalizability and the accuracy of geological identification. First, a k-means algorithm is used to redefine the stratum based on the key mechanical indexes of strata. An XGBoost model is then used to determine the stratum composition of the excavation face based on the tunnelling parameters. If the result is compound strata, a deep neural network with an attention mechanism is used to predict the percentage of each stratum. The attention mechanism assigns weights to the features of the tunnelling parameters according to the stratum composition. The simulation results in the interval between Qian-Zhuang and Ke-Ning Road of Nanjing Metro show that the method can effectively determine the geological conditions on the excavation face. Furthermore, the method was used in the Hangzhou-Shaoxing intercity railroad tunnel project, where the 'ZhiYu' self-driving shield was used for tunnelling control. It helped the 'ZhiYu' shield to adjust the construction parameters quickly and improve the safety and quality of the project.
Complex optical transport, dynamics, and rheology of intermediately attractive emulsions
Authors: Xu Yixuan , Mason Thomas G. 
Published: January 2023

AbstractIntroducing short-range attractions in Brownian systems of monodisperse colloidal spheres can substantially impact their structures and consequently their optical transport and rheological properties. Here, for size-fractionated colloidal emulsions, we show that imposing an intermediate strength of attraction, well above but not much larger than thermal energy ($$\approx 5.6$$

≈
5.6

$$k_{\textrm{B}}T)$$

k
B

T
)

, through micellar depletion leads to a striking notch in the measured inverse mean free path of optical transport, $$1/\ell ^*$$

1
/

ℓ
∗

, as a function of droplet volume fraction, $$\phi$$
ϕ
. This notch, which appears between the hard-sphere glass transition, $$\phi _{\textrm{g}}$$

ϕ
g

, and maximal random jamming, $$\phi _{\textrm{MRJ}}$$

ϕ
MRJ

, implies the existence of a greater population of compact dense clusters of droplets, as compared to tenuous networks of droplets in strongly attractive emulsion gels. We extend a prior decorated core-shell network model for strongly attractive colloidal systems to include dense non-percolating clusters that do not contribute to shear rigidity. By constraining this extended model using the measured $$1/\ell ^*(\phi )$$

1
/

ℓ
∗

(
ϕ
)

, we improve and expand the microrheological interpretation of diffusing wave spectroscopy (DWS) experiments made on attractive colloidal systems. Our measurements and modeling demonstrate richness and complexity in optical transport and shear rheological properties of dense, disordered colloidal systems having short-range intermediate attractions between moderately attractive glasses and strongly attractive gels.
Influence of social deprivation index on in-hospital outcomes of COVID-19
Authors: Goyal Parag , Schenck Edward , Wu Yiyuan , Zhang Yongkang , Visaria Aayush , Orlander Duncan , Xi Wenna , Díaz Iván , Morozyuk Dmitry , Weiner Mark , Kaushal Rainu , Banerjee Samprit 
Published: January 2023

AbstractWhile it is known that social deprivation index (SDI) plays an important role on risk for acquiring Coronavirus Disease 2019 (COVID-19), the impact of SDI on in-hospital outcomes such as intubation and mortality are less well-characterized. We analyzed electronic health record data of adults hospitalized with confirmed COVID-19 between March 1, 2020 and February 8, 2021 from the INSIGHT Clinical Research Network (CRN). To compute the SDI (exposure variable), we linked clinical data using patient’s residential zip-code with social data at zip-code tabulation area. SDI is a composite of seven socioeconomic characteristics determinants at the zip-code level. For this analysis, we categorized SDI into quintiles. The two outcomes of interest were in-hospital intubation and mortality. For each outcome, we examined logistic regression and random forests to determine incremental value of SDI in predicting outcomes. We studied 30,016 included COVID-19 patients. In a logistic regression model for intubation, a model including demographics, comorbidity, and vitals had an Area under the receiver operating characteristic curve (AUROC) = 0.73 (95% CI 0.70–0.75); the addition of SDI did not improve prediction [AUROC = 0.73 (95% CI 0.71–0.75)]. In a logistic regression model for in-hospital mortality, demographics, comorbidity, and vitals had an AUROC = 0.80 (95% CI 0.79–0.82); the addition of SDI in Model 2 did not improve prediction [AUROC = 0.81 (95% CI 0.79–0.82)]. Random forests revealed similar findings. SDI did not provide incremental improvement in predicting in-hospital intubation or mortality. SDI plays an important role on who acquires COVID-19 and its severity; but once hospitalized, SDI appears less important.
Superhydrophobic and oleophobic microtextured aluminum surface with long durability under corrosive environment
Authors: Adarraga Olatz , Agustín-Sáenz Cecilia , Bustero Izaskun , Brusciotti Fabiola 
Published: January 2023

AbstractSuperhydrophobic (SHP) and oleophobic aluminum surfaces have been prepared through the combination of a scalable chemical microtexturing process and surface functionalization with long-chained polyfluoroalkyl moieties. The effect of an anodic layer on the microtextured surface has been assessed considering surface morphology, superhydrophobicity, surface mechanical properties and corrosion protection enhancement. The surface functionalization with polyfluoroalkyl moieties has been tackled in two different ways: (i) grafting of the polyfluoroalkyl moieties and (ii) deposition of a thin hybrid coating with low content of polyfluoroalkyl-containing compound. Aluminum surfaces showing high durability in salt spray environments, which maintain SHP and oleophobic properties at least up to 2016 h have been attained. Applications for this kind of surfaces range from easy-to-clean surfaces to anti-icing or anti-condensation functionalities that could be of interest for several sectors.
Prevalence of computer vision syndrome: a systematic review and meta-analysis
Authors: Anbesu Etsay Woldu , Lema Asamene Kelelom 
Published: January 2023

AbstractAlthough computer vision syndromes are becoming a major public health concern, less emphasis is given to them, particularly in developing countries. There are primary studies on different continents; however, there are inconsistent findings in prevalence among the primary studies. Therefore, this systematic review and meta-analysis aimed to estimate the pooled prevalence of computer vision syndrome. In this study, the review was developed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Online electronic databases, including PubMed/Medline, CINAHL, and Google Scholar, were used to retrieve published and unpublished studies. The study was conducted from December 1 to April 9/2022. Study selection, quality assessment, and data extraction were performed independently by two authors. Quality assessment of the studies was performed using the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument tool. Heterogeneity was assessed using the statistical test I2. STATA 14 software was used for statistical analysis. A total of 7,35 studies were retrieved, and 45 studies were included in the final meta-analysis. The pooled prevalence of computer vision syndrome was 66% (95% CI: 59, 74). Subgroup analysis based on country was highest in Pakistan (97%, 95% CI: 96, 98) and lowest in Japan (12%, 95% CI: 9, 15). Subgroup analysis based on country showed that studies in Saudi Arabia (I2 = 99.41%,pvalue < 0.001), Ethiopia (I2 = 72.6%,pvalue < 0.001), and India (I2 = 98.04%,pvalue < 0.001) had significant heterogeneity. In the sensitivity analysis, no single study unduly influenced the overall effect estimate. Nearly two in three participants had computer vision syndrome. Thus, preventive practice strategic activities for computer vision syndrome are important interventions.
Integrated multiomics analysis to infer COVID-19 biological insights
Authors: Sameh Mahmoud , Khalaf Hossam M. , Anwar Ali Mostafa , Osama Aya , Ahmed Eman Ali , Mahgoub Sebaey , Ezzeldin Shahd , Tanios Anthony , Alfishawy Mostafa , Said Azza Farag , Mohamed Maged Salah , Sayed Ahmed A. , Magdeldin Sameh 
Published: January 2023

AbstractThree years after the pandemic, we still have an imprecise comprehension of the pathogen landscape and we are left with an urgent need for early detection methods and effective therapy for severe COVID-19 patients. The implications of infection go beyond pulmonary damage since the virus hijacks the host's cellular machinery and consumes its resources. Here, we profiled the plasma proteome and metabolome of a cohort of 57 control and severe COVID-19 cases using high-resolution mass spectrometry. We analyzed their proteome and metabolome profiles with multiple depths and methodologies as conventional single omics analysis and other multi-omics integrative methods to obtain the most comprehensive method that portrays an in-depth molecular landscape of the disease. Our findings revealed that integrating the knowledge-based and statistical-based techniques (knowledge-statistical network) outperformed other methods not only on the pathway detection level but even on the number of features detected within pathways. The versatile usage of this approach could provide us with a better understanding of the molecular mechanisms behind any biological system and provide multi-dimensional therapeutic solutions by simultaneously targeting more than one pathogenic factor.
Morphological, immunohistochemical, and biochemical study on the ameliorative effect of gallic acid against bisphenol A-induced nephrotoxicity in male albino rats
Authors: Saleh Shaimaa M. M. , Mahmoud A. Bakr , Al-Salahy M. Bassam , Mohamed Moustafa Fatma Ahmed 
Published: January 2023

AbstractThis study aimed to determine the effect of gallic acid (GA) on ameliorating bisphenol A (BPA) nephrotoxicity in male rat kidneys. Forty rats were assigned randomly into two groups: control (ten animals) and BPA (40 mg/kg bwt) (thirty animals), the second group was divided into three subgroups: BPA alone, BPA + G50 (50 mg/kg bwt), and BPA + G200 (200 mg/kg bwt). The biochemical analysis included measurements of the contents of nitric oxide, lipid peroxidation, reactive oxygen species, and cytokines (interleukin-1α and interleukin-6) in the kidney. The antioxidant enzymes catalase and superoxide dismutase were also measured in the kidney. Kidney function was assessed by determining uric acid, urea, and creatinine levels. The morphological investigations included hematoxylin and eosin staining for assessing the general histology and determining the glomerular and corpuscular areas, the tubular cell degeneration mean area, and the mean leukocyte infiltration area. Also, collagen fiber intensity and polysaccharide content were analyzed. Furthermore, immunohistochemical, morphometric, and ultrastructural studies were carried out. The results revealed morphological, immunohistochemical, and biochemical alterations in the kidney. Most of these changes showed a satisfactory improvement of kidney damage when BPA-administered rats were treated with GA at both doses. In conclusion, GA exhibited a strong protective effect against BPA-induced nephrotoxicity.
Persistent reshaping of cohesive sediment towards stable flocs by turbulence
Authors: Yu Minglan , Yu Xiao , Mehta Ashish J. , Manning Andrew J. , Khan Faisal , Balachandar S. 
Published: January 2023

AbstractCohesive sediment forms flocs of various sizes and structures in the natural turbulent environment. Understanding flocculation is critical in accurately predicting sediment transport and biogeochemical cycles. In addition to aggregation and breakup, turbulence also reshapes flocs toward more stable structures. An Eulerian–Lagrangian framework has been implemented to investigate the effect of turbulence on flocculation by capturing the time-evolution of individual flocs. We have identified two floc reshaping mechanisms, namely breakage-regrowth and restructuring by hydrodynamic drag. Surface erosion is found to be the primary breakup mechanism for strong flocs, while fragile flocs tend to split into fragments of similar sizes. Aggregation of flocs of sizes comparable to or greater than the Kolmogorov scale is modulated by turbulence with lower aggregation efficiency. Our findings highlight the limiting effects of turbulence on both floc size and structure.
Quantifying microstructures of earth materials using higher-order spatial correlations and deep generative adversarial networks
Authors: Amiri Hamed , Vasconcelos Ivan , Jiao Yang , Chen Pei-En , Plümper Oliver 
Published: January 2023

AbstractThe key to most subsurface processes is to determine how structural and topological features at small length scales, i.e., the microstructure, control the effective and macroscopic properties of earth materials. Recent progress in imaging technology has enabled us to visualise and characterise microstructures at different length scales and dimensions. However, one limitation of these technologies is the trade-off between resolution and sample size (or representativeness). A promising approach to this problem is image reconstruction which aims to generate statistically equivalent microstructures but at a larger scale and/or additional dimension. In this work, a stochastic method and three generative adversarial networks (GANs), namely deep convolutional GAN (DCGAN), Wasserstein GAN with gradient penalty (WGAN-GP), and StyleGAN2 with adaptive discriminator augmentation (ADA), are used to reconstruct two-dimensional images of two hydrothermally rocks with varying degrees of complexity. For the first time, we evaluate and compare the performance of these methods using multi-point spatial correlation functions—known as statistical microstructural descriptors (SMDs)—ultimately used as external tools to the loss functions. Our findings suggest that a well-trained GAN can reconstruct higher-order, spatially-correlated patterns of complex earth materials, capturing underlying structural and morphological properties. Comparing our results with a stochastic reconstruction method based on a two-point correlation function, we show the importance of coupling training/assessment of GANs with higher-order SMDs, especially in the case of complex microstructures. More importantly, by quantifying original and reconstructed microstructures via different GANs, we highlight the interpretability of these SMDs and show how they can provide valuable insights into the spatial patterns in the synthetic images, allowing us to detect common artefacts and failure cases in training GANs.
Predicting the potential suitable distribution area of Emeia pseudosauteri in Zhejiang Province based on the MaxEnt model
Authors: Li Sheng , Wang Zesheng , Zhu Zhixin , Tao Yizhou , Xiang Jie 
Published: January 2023

AbstractHuman activities, including urbanization, industrialization, agricultural pollution, and land use, have contributed to the increased fragmentation of natural habitats and decreased biodiversity in Zhejiang Province as a result of socioeconomic development. Numerous studies have demonstrated that the protection of ecologically significant species can play a crucial role in restoring biodiversity. Emeia pseudosauteri is regarded as an excellent environmental indicator, umbrella and flagship species because of its unique ecological attributes and strong public appeal. Assessing and predicting the potential suitable distribution area of this species in Zhejiang Province can help in the widespread conservation of biodiversity. We used the MaxEnt ecological niche model to evaluate the habitat suitability of E. pseudosauteri in Zhejiang Province to understand the potential distribution pattern and environmental characteristics of suitable habitats for this species, and used the AUC (area under the receiver operating characteristic curve) and TSS (true skill statistics) to evaluate the model performance. The results showed that the mean AUC value was 0.985, the standard deviation was 0.011, the TSS average value was 0.81, and the model prediction results were excellent. Among the 11 environmental variables used for modeling, temperature seasonality (Bio_4), altitude (Alt) and distance to rivers (Riv_dis) were the key variables affecting the distribution area of E. pseudosauteri, with contributions of 33.5%, 30% and 15.9%, respectively. Its main suitable distribution area is in southern Zhejiang Province and near rivers, at an altitude of 50–300 m, with a seasonal variation in temperature of 7.7–8 °C. Examples include the Ou River, Nanxi River, Wuxi River, and their tributary watersheds. This study can provide a theoretical basis for determining the scope of E. pseudosauteri habitat protection, population restoration, resource management and industrial development in local areas.