bluuebunny/crossref_metadata_2025_split huggingface dataset:
Traditional and novel time-series approaches reveal submarine groundwater discharge dynamics under baseline and extreme event conditions
Authors: McKenzie Tristan , Dulai Henrietta , Fuleky Peter 
Published: November 2021

AbstractGroundwater is a vital resource for humans and groundwater dependent ecosystems. Coastal aquifers and submarine groundwater discharge (SGD), both influenced by terrestrial and marine forces, are increasingly affected by climate variations and sea-level rise. Despite this, coastal groundwater resources and discharge are frequently poorly constrained, limiting our understanding of aquifer responses to external forces. We apply traditional and novel time-series approaches using an SGD dataset of previously unpublished resolution and duration, to analyze the dependencies between precipitation, groundwater level, and SGD at a model site (Kīholo Bay, Hawaiʻi). Our objectives include (1) determining the relative contribution of SGD drivers over tidal and seasonal periods, (2) establishing temporal relationships and thresholds of processes influencing SGD, and (3) evaluating the impacts of anomalous events, such as tropical storms, on SGD. This analysis reveals, for example, that precipitation is only a dominant influence during wet periods, and otherwise tides and waves dictate the dynamics of SGD. It also provides time lags between intense storm events and higher SGD rates, as well as thresholds for precipitation, wave height and tides affecting SGD. Overall, we demonstrate an approach for modeling a hydrological system while elucidating coastal aquifer and SGD response in unprecedented detail.
A study of the subdiffusion of small molecules in charged polyelectrolyte multilayers
Authors: Vardanyan I. , Arakelyan V. , Navoyan Z. , Diamanti Eleftheria , Moya S. E. , Donath E. 
Published: November 2021

AbstractA theoretical approach has been developed here to describe the slow diffusion of small charged molecules of sodium dithionite (S2O42−) in polyelectrolyte multilayers (PEMs) composed of polyallylamine hydrochloride (PAH) and polystyrene sulfonate (PSS), which is demonstrated here to be a case of subdifussion. Diffusion is measured experimentally by recording the quenching of the fluorescence of (7-nitrobenz-2-oxa-1,3-diazol-4yl) amino (NBD) labelled PAH layers assembled on silica particles by flow cytometry. NBD is reduced when it encounters dithionite leading to the disappearance of the fluorescence. The fluorescence decay curves show a slow diffusion of dithionite, that does not follow classical Fickean law. Dithionite diffusion in the PEMs is shown to be a non-Markovian process and the slow diffusion can be described via diffusion equations with fractional time derivatives. Results are explained assuming subdifussion of dithionite in the PEMs, as a result of the trapping of the negatively charged dithionite in the positively charged layers of PAH.
A weighted patient network-based framework for predicting chronic diseases using graph neural networks
Authors: Lu Haohui , Uddin Shahadat 
Published: November 2021

AbstractChronic disease prediction is a critical task in healthcare. Existing studies fulfil this requirement by employing machine learning techniques based on patient features, but they suffer from high dimensional data problems and a high level of bias. We propose a framework for predicting chronic disease based on Graph Neural Networks (GNNs) to address these issues. We begin by projecting a patient-disease bipartite graph to create a weighted patient network (WPN) that extracts the latent relationship among patients. We then use GNN-based techniques to build prediction models. These models use features extracted from WPN to create robust patient representations for chronic disease prediction. We compare the output of GNN-based models to machine learning methods by using cardiovascular disease and chronic pulmonary disease. The results show that our framework enhances the accuracy of chronic disease prediction. The model with attention mechanisms achieves an accuracy of 93.49% for cardiovascular disease prediction and 89.15% for chronic pulmonary disease prediction. Furthermore, the visualisation of the last hidden layers of GNN-based models shows the pattern for the two cohorts, demonstrating the discriminative strength of the framework. The proposed framework can help stakeholders improve health management systems for patients at risk of developing chronic diseases and conditions.
Thermo-vibrational analyses of skin tissue subjected to laser heating source in thermal therapy
Authors: Ghanbari Mina , Rezazadeh Ghader 
Published: November 2021

AbstractLaser-induced thermal therapy, due to its applications in various clinical treatments, has become an efficient alternative, especially for skin ablation. In this work, the two-dimensional thermomechanical response of skin tissue subjected to different types of thermal loading is investigated. Considering the thermoelastic coupling term, the two-dimensional differential equation of heat conduction in the skin tissue based on the Cattaneo–Vernotte heat conduction law is presented. The two-dimensional differential equation of the tissue displacement coupled with the two-dimensional hyperbolic heat conduction equation in the tissue is solved simultaneously to analyze the thermal and mechanical response of the skin tissue. The existence of mixed complicated boundary conditions makes the problem so complex and intricate. The Galerkin-based reduced-order model has been utilized to solve the two-sided coupled differential equations of vibration and heat transfer in the tissue with accompanying complicated boundary conditions. The effect of various types of heating sources such as thermal shock, single and repetitive pulses, repeating sequence stairs, ramp-type, and harmonic-type heating, on the thermomechanical response of the tissue is investigated. The temperature distribution in the tissue along depth and radial direction is also presented. The transient temperature and displacement response of tissue considering different relaxation times are studied, and the results are discussed in detail.
Evaluation and selection of potent fluorescent immunosensors by combining fluorescent peptide and nanobodies displayed on yeast surface
Authors: Inoue Akihito , Yasuda Takanobu , Zhu Bo , Kitaguchi Tetsuya , Murakami Akikazu , Ueda Hiroshi 
Published: November 2021

AbstractQuenchbody (Q-body) is a quench-based fluorescent immunosensor labeled with fluorescent dye(s) near the antigen-binding site of an antibody. Q-bodies can detect a range of target molecules rapidly and directly. However, because Q-bodies show different antigen responses depending on the antibody used, time-consuming optimization of the Q-body structure is often necessary, and a high-throughput screening method for discriminating and selecting good Q-bodies is required. Here, we aimed to develop a molecular display method of nanobody-based “mini Q-bodies” by combining yeast surface display and coiled-coil forming E4/K4 peptide-based fluorescence labeling. As a result, the yeast-displayed mini Q-body recognizing the anti-cancer agent methotrexate (MTX) showed significant quenching and MTX-dependent dequenching on cells. To demonstrate the applicability of the developed method to select highly responsive mini Q-bodies, a small nanobody library consisting of 30 variants that recognize human serum albumin was used as a model. The best variant, showing a 2.4-fold signal increase, was obtained through selection by flow cytometry. Furthermore, the same nanobody prepared fromEscherichia colialso worked as a mini Q-body after dye labeling. The described approach will be applied to quickly obtain well-behaved Q-bodies and other fluorescent biosensors for various targets through directed evolutionary approaches.
Measurements of spontaneous CFTR-mediated ion transport without acute channel activation in airway epithelial cultures after modulator exposure
Authors: Nick Heidi J. , Zeitlin Pamela L. , Yadav Sangya , Bratcher Preston E. 
Published: November 2021

AbstractQuantitation of CFTR function in vitro is commonly performed by acutely stimulating then inhibiting ion transport through CFTR and measuring the resulting changes in transepithelial voltage (Vte) and current (ISC). While this technique is suitable for measuring the maximum functional capacity of CFTR, it may not provide an accurate estimate of in vivo CFTR activity. To test if CFTR-mediated ion transport could be measured in the absence of acute CFTR stimulation, primary airway epithelia were analyzed in an Ussing chamber with treatment of amiloride followed by CFTR(inh)-172 without acute activation of CFTR. Non-CF epithelia demonstrated a decrease in Vte and ISC following exposure to CFTR(inh)-172 and in the absence of forskolin/IBMX (F/I); this decrease is interpreted as a measure of spontaneous CFTR activity present in these epithelia. In F508del/F508del CFTR epithelia, F/I-induced changes in Vte and ISC were ~ fourfold increased after treatment with VX-809/VX-770, while the magnitude of spontaneous CFTR activities were only ~ 1.6-fold increased after VX-809/VX-770 treatment. Method-dependent discrepancies in the responses of other CF epithelia to modulator treatments were observed. These results serve as a proof of concept for the analysis of CFTR modulator responses in vitro in the absence of acute CFTR activation. Future studies will determine the usefulness of this approach in the development of novel CFTR modulator therapies.
Serum FGF21 levels are altered by various factors including lifestyle behaviors in male subjects
Authors: Nakanishi Kaori , Ishibashi Chisaki , Ide Seiko , Yamamoto Ryohei , Nishida Makoto , Nagatomo Izumi , Moriyama Toshiki , Yamauchi-Takihara Keiko 
Published: November 2021

AbstractFibroblast growth factor (FGF) 21 has various functions, including glucose and lipid metabolism. This cross-sectional study aimed to investigate specific conditions that might influence the functions of FGF21. 398 men who underwent a health examination were enrolled in this study. Physical and biochemical parameters and information on several lifestyle behaviors were obtained from all subjects. FGF21 levels correlated with age, body mass index (BMI), waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transpeptidase (γ-GTP), uric acid, total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDLC), fasting plasma glucose (FPG), and HbA1c. Moreover, FGF21 levels were significantly associated with lifestyle behaviors, including smoking status and breakfast and alcohol consumption frequency. Multivariable regression analysis showed that age, ALT, γ-GTP, smoking status, and breakfast and alcohol consumption frequency were independent variables for FGF21 levels. Assessment among the non-obese and obese groups showed that FGF21 levels correlated with WC, SBP, and TC only in the non-obese group. Thus, serum FGF21 levels were affected by several factors, including lifestyle behaviors, age, and liver function. To assess the functions of FGF21 in individuals, considering these factors would be essential.
LDL-cholesterol trajectories and statin treatment in Finnish type 2 diabetes patients: a growth mixture model
Authors: Inglin Laura , Lavikainen Piia , Jalkanen Kari , Laatikainen Tiina 
Published: November 2021

AbstractWe aimed to identify distinct longitudinal trends of LDL-cholesterol (LDL-C) levels and investigate these trajectories’ association with statin treatment. This retrospective cohort study used electronic health records from 8592 type 2 diabetes patients in North Karelia, Finland, comprising all primary and specialised care visits 2011‒2017. We compared LDL-C trajectory groups assessing LDL-C treatment target achievement and changes in statin treatment intensity. Using a growth mixture model, we identified four LDL-C trajectory groups. The majority (85.9%) had “moderate-stable” LDL-C levels around 2.3 mmol/L. The second-largest group (7.7%) consisted of predominantly untreated patients with alarmingly “high-stable” LDL-C levels around 3.9 mmol/L. The “decreasing” group (3.8%) was characterised by large improvements in initially very high LDL-C levels, along with the highest statin treatment intensification rates, while among patients with “increasing” LDL-C (2.5%), statin treatment declined drastically. In all the trajectory groups, women had significantly higher average LDL-C levels and received less frequent any statin treatment and high-intensity treatment than men. Overall, 41.9% of patients had no statin prescribed at the end of follow-up. Efforts to control LDL-C should be increased—especially in patients with continuously elevated levels—by initiating and intensifying statin treatment earlier and re-initiating the treatment after discontinuation if possible.
Impact of the molar activity and PSMA expression level on [18F]AlF-PSMA-11 uptake in prostate cancer
Authors: Piron Sarah , Verhoeven Jeroen , De Coster Emma , Descamps Benedicte , Kersemans Ken , Pieters Leen , Vral Anne , Vanhove Christian , De Vos Filip 
Published: November 2021

AbstractThis two-part preclinical study aims to evaluate prostate specific membrane antigen (PSMA) as a valuable target for expression-based imaging applications and to determine changes in target binding in function of varying apparent molar activities (MAapp) of [18F]AlF-PSMA-11. For the evaluation of PSMA expression levels, male NOD/SCID mice bearing prostate cancer (PCa) xenografts of C4-2 (PSMA+++), 22Rv1 (PSMA+) and PC-3 (PSMA−) were administered [18F]AlF-PSMA-11 with a medium MAapp (20.24 ± 3.22 MBq/nmol). SUVmean and SUVmax values were respectively 3.22 and 3.17 times higher for the high versus low PSMA expressing tumors (p < 0.0001). To evaluate the effect of varying MAapp, C4-2 and 22Rv1 xenograft bearing mice underwent additional [18F]AlF-PSMA-11 imaging with a high (211.2 ± 38.9 MBq/nmol) and/or low MAapp (1.92 ± 0.27 MBq/nmol). SUV values showed a significantly increasing trend with higher MAapp. Significant changes were found for SUVmean and SUVmax between the high versus low MAapp and medium versus low MAapp (both p < 0.05), but not between the high versus medium MAapp (p = 0.055 and 0.25, respectively). The effect of varying MAapp was more pronounced in low expressing tumors and PSMA expressing tissues (e.g. salivary glands and kidneys). Overall, administration of a high MAapp increases the detection of low expression tumors while also increasing uptake in PSMA expressing tissues, possibly leading to false positive findings. In radioligand therapy, a medium MAapp could reduce radiation exposure to dose-limiting organs with only limited effect on radionuclide accumulation in the tumor.
Investigation of SARS-CoV-2 inactivation using UV-C LEDs in public environments via ray-tracing simulation
Authors: Lai Po-Yen , Liu Huizhe , Ng Ray Jia Hong , Wint Hnin Thet Bianca , Chu Hong-Son , Teo Jin Wah Ronnie , Ong Qunxiang , Liu Yuanjie , Png Ching Eng 
Published: November 2021

AbstractThis paper proposes an investigating SARS-CoV-2 inactivation on surfaces with UV-C LED irradiation using our in-house-developed ray-tracing simulator. The results are benchmarked with experiments and Zemax OpticStudio commercial software simulation to demonstrate our simulator's easy accessibility and high reliability. The tool can input the radiant profile of the flexible LED source and accurately yield the irradiance distribution emitted from an LED-based system in 3D environments. The UV-C operating space can be divided into the safe, buffer, and germicidal zones for setting up a UV-C LED system. Based on the published measurement data, the level of SARS-CoV-2 inactivation has been defined as a function of UV-C irradiation. A realistic case of public space, i.e., a food court in Singapore, has been numerically investigated to demonstrate the relative impact of environmental UV-C attenuation on the SARS-CoV-2 inactivation. We optimise a specific UV-C LED germicidal system and its corresponding exposure time according to the simulation results. These ray-tracing-based simulations provide a useful guideline for safe deployment and efficient design for germicidal UV-C LED technology.
Association between depression and the risk of Alzheimer’s disease using the Korean National Health Insurance Service-Elderly Cohort
Authors: Kim Hyunkyu , Jeong Wonjeong , Kwon Junhyun , Kim Youseok , Park Eun-Cheol , Jang Sung-In 
Published: November 2021

AbstractIn this cohort study, we assessed the association between depression and the risk of Alzheimer’s disease from data obtained from the 2002 to 2013 Korean National Health Insurance Service-Elderly Cohort Database, which accounts for 10% of the South Korean population aged > 60 years. A total 518,466 patients were included in the analysis and followed up, unless they were excluded due to death or migration. Patients who sought treatment for depression or dementia within 1 year of the washout period and who were diagnosed with dementia within the 1-year period of the diagnosis of depression were excluded from the study. The risk of dementia was analysed using Cox proportional hazards models. Patients with a history of depression during the follow-up period were at a higher risk of Alzheimer’s disease than those without a history of depression (HR 3.35, CI 3.27–3.42). The severe-depression group exhibited the highest risk of Alzheimer’s disease (HR 4.41, CI 4.04–4.81), while the mild-depression group exhibited a relatively lower risk of Alzheimer’s disease (HR 3.31, CI 3.16–3.47). The risk of Alzheimer’s disease was associated with depression history and an increased severity of depression increased the risk of Alzheimer’s disease.
Integrated intelligent computing application for effectiveness of Au nanoparticles coated over MWCNTs with velocity slip in curved channel peristaltic flow
Authors: Raja Muhammad Asif Zahoor , Sabati Mohammad , Parveen Nabeela , Awais Muhammad , Awan Saeed Ehsan , Chaudhary Naveed Ishtiaq , Shoaib Muhammad , Alquhayz Hani 
Published: November 2021

AbstractEstimation of the effectiveness of Au nanoparticles concentration in peristaltic flow through a curved channel by using a data driven stochastic numerical paradigm based on artificial neural network is presented in this study. In the modelling, nano composite is considered involving multi-walled carbon nanotubes coated with gold nanoparticles with different slip conditions. Modeled differential system of the physical problem is numerically analyzed for different scenarios to predict numerical data for velocity and temperature by Adams Bashforth method and these solutions are used as a reference dataset of the networks. Data is processed by segmentation into three categories i.e., training, validation and testing while Levenberg–Marquart training algorithm is adopted for optimization of networks results in terms of performance on mean square errors, train state plots, error histograms, regression analysis, time series responses, and auto-correlation, which establish the accurate and efficient recognition of trends of the system.
Correlated iron isotopes and silicon contents in aubrite metals reveal structure of their asteroidal parent body
Authors: Ray Soumya , Garvie Laurence A. J. , Rai Vinai K. , Wadhwa Meenakshi 
Published: November 2021

AbstractIron isotopes record the physical parameters, such as temperature and redox conditions, during differentiation processes on rocky bodies. Here we report the results of a correlated investigation of iron isotope compositions and silicon contents of silicon-bearing metal grains from several aubritic meteorites. Based on their Fe isotopic and elemental Si compositions and thermal modelling, we show that these aubrite metals equilibrated with silicates at temperatures ranging from ~ 1430 to ~ 1640 K and likely sampled different depths within their asteroidal parent body. The highest temperature in this range corresponds to their equilibration at a minimum depth of up to ~ 35 km from the surface of the aubrite parent body, followed by brecciation and excavation by impacts within the first ~ 4 Myr of Solar System history.
PremPLI: a machine learning model for predicting the effects of missense mutations on protein-ligand interactions
Authors: Sun Tingting , Chen Yuting , Wen Yuhao , Zhu Zefeng , Li Minghui 
Published: November 2021

AbstractResistance to small-molecule drugs is the main cause of the failure of therapeutic drugs in clinical practice. Missense mutations altering the binding of ligands to proteins are one of the critical mechanisms that result in genetic disease and drug resistance. Computational methods have made a lot of progress for predicting binding affinity changes and identifying resistance mutations, but their prediction accuracy and speed are still not satisfied and need to be further improved. To address these issues, we introduce a structure-based machine learning method for quantitatively estimating the effects of single mutations on ligand binding affinity changes (named as PremPLI). A comprehensive comparison of the predictive performance of PremPLI with other available methods on two benchmark datasets confirms that our approach performs robustly and presents similar or even higher predictive accuracy than the approaches relying on first-principle statistical mechanics and mixed physics- and knowledge-based potentials while requires much less computational resources. PremPLI can be used for guiding the design of ligand-binding proteins, identifying and understanding disease driver mutations, and finding potential resistance mutations for different drugs. PremPLI is freely available athttps://lilab.jysw.suda.edu.cn/research/PremPLI/and allows to do large-scale mutational scanning.
Fissisternoids A and B, two 2′,5′-quinodihydrochalcone-based meroterpenoid enantiomers with unusual carbon skeletons from Fissistigma bracteolatum
Authors: Xue Gui-Min , Zhao Chen-Guang , Xue Jin-Feng , Chen Hui , Zhao Zhen-Zhu , Si Ying-Ying , Du Kun , Zhi Yan-Le , Feng Wei-Sheng 
Published: November 2021

Compound 1 represents an unprecedented meroterpenoid featuring a unique tricyclo [3,3,1,01′,5′] decane central framework and 2 possesses a rare 6/6/5/4 tetracyclic carbon skeleton were isolated from Fissistigma bracteolatum.