bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between nonalcoholic fatty liver disease and peripheral neuropathy in US population, a cross-sectional study
Authors: Gu Xi , Tang Dou , Xuan Yan , Shen Ying , Lu Lei Qun 
Published: April 2023

AbstractNonalcoholic fatty liver disease (NAFLD) has become an important risk of type 2 diabetes mellitus (T2DM). Peripheral neuropathy (PN) is regarded as one of the main microvascular complications of diabetes. But the association of NAFLD with PN is still unclear. We aimed to investigate the association between NAFLD and PN in US population by conducting a cross-sectional study. We enrolled 3029 participants aged 40–85 years from National Health and Nutrition Examination Survey (NHANES) 1999–2004. NAFLD was defined as a US Fatty Liver Index (FLI) score ≥ 30, and PN was defined as having one or more insensate areas on either foot. Participants were divided into two groups (with or without PN). We performed multivariate logistic regression models to evaluate the association between NAFLD and PN. Subgroup analyses were used to find out whether the association was stable in different stratified groups. Sensitivity analyses were conducted to assess the robustness of the results. All the analyses were weighted. Among the individuals, 524 (17.3%) had PN and 1250 (41.27%) had NAFLD. In the multivariate logistic regression models, NAFLD was associated with an increased risk of PN (OR 1.44 [1.03 ~ 2.02]) after fully adjusting for covariates. In the subgroup analyses, NAFLD was significantly associated with PN in the age group (40–64 years), compared with those in the age group (65–85 years), (P for interaction: 0.004). The results of association of NAFLD with PN were stable in sensitivity analyses. In this cross-sectional study among US adults aged 40–85 years old, NAFLD was associated with an increased likelihood of prevalent PN.
Metabolic profiling, antioxidant, and enzyme inhibition potential of Iris pseudacorus L. from Egypt and Japan: A comparative study
Authors: Yehia Suzan M. , Ayoub Iriny M. , Watanabe Masato , Devkota Hari Prasad , Singab Abdel Nasser B. 
Published: April 2023

AbstractGenus Iris comprises numerous and diverse phytoconstituents displaying marked biological activities. The rhizomes, and aerial parts of Iris pseudacorus L. cultivars from Egypt and Japan were subjected to comparative metabolic profiling using UPLC-ESI-MS/MS. The antioxidant capacity was determined using DPPH assay. In vitro enzyme inhibition potential against α-glucosidase, tyrosinase and lipase was evaluated. In silico molecular docking was conducted on the active sites of human α-glucosidase and human pancreatic lipase. Forty-three compounds were tentatively identified including flavonoids, isoflavonoids, phenolics and xanthones. I. pseudacorus rhizomes extracts (IPR-J and IPR-E) exhibited the highest radical scavenging activity with IC50 values of 40.89 µg/mL and 97.97 µg/mL, respectively (Trolox IC50 value was 14.59 µg/mL). Moreover, IPR-J and IPR-E exhibited promising α-glucosidase inhibitory activity displaying IC50 values of 18.52 µg/mL, 57.89 µg/mL, respectively being more potent as compared to acarbose with IC50 value of 362.088 µg/mL. All extracts exerted significant lipase inhibitory activity exhibiting IC50 values of 2.35, 4.81, 2.22 and 0.42 µg/mL, respectively compared to cetilistat with IC50 value of 7.47 µg/mL. However, no tyrosinase inhibitory activity was observed for all I. pseudacorus extracts up to 500 µg/mL. In silico molecular modelling revealed that quercetin, galloyl glucose, and irilin D exhibited the highest fitting scores within the active sites of human α-glucosidase and pancreatic lipase. ADMET prediction (absorption, distribution, metabolism, excretion, and toxicity) showed that most of the phytoconstituents exhibited promising pharmacokinetic, pharmacodynamics and tolerable toxicity properties. According to our findings, I. pseudacorus might be considered as a valuable source for designing novel phytopharmaceuticals.
Facies evaluation and sedimentary environments of the Yamama Formation in the Ratawi oil field, South Iraq
Authors: Al-Iessa Israa A. , Zhang Wang Zhi 
Published: April 2023

AbstractMicrofacies and environmental analyses of the Yamama Formation were conducted in the Tithonian–Hautervian sequence in the Ratawi oil field of Basra city in southern Iraq. The study includes petrographic, facies, and depositional models for the study area. Seven main facies and several secondary facies have been deposited in multiple environments. Moreover, they are affected by many diagenesis processes. Those facies have noncore depths that can be monitored by matching them with their corresponding well logs to obtain their electrofacies. The facies are distinguished according to the grain or mud supported or on the appearance of the configuration facies through microscopy. After comparing them with the well logs, electrofacies are identified as the following main limestone facies (mudstone, mudstone–wackestone, wackestone, wackestone–packstone, packstone, packstone–grainstone, and grainstone facies). The formation environments in this field are divided into several environments depending on the facies and electrofacies characteristics of the formation, including a lagoon environment, open marine environment, shoal environment, and slope environment.
Sulfur and nitrogen co-doped carbon quantum dots as fluorescent probes for the determination of some pharmaceutically-important nitro compounds
Authors: Magdy Galal , Ebrahim Shaimaa , Belal Fathalla , El-Domany Ramadan A. , Abdel-Megied Ahmed M. 
Published: April 2023

AbstractIn this study, highly fluorescent sulfur and nitrogen co-doped carbon quantum dots (SN-CQDs) were synthesized by a simple one-pot hydrothermal method using thiosemicarbazide and citric acid as starting materials. Various spectroscopic and microscopic techniques were applied to characterize the prepared SN-CQDs. The synthesized SN-CQDs’ maximum fluorescence emission was obtained at 430 nm after excitation at 360 nm. Rifampicin (RFP), tinidazole (TNZ), ornidazole (ONZ), and metronidazole (MNZ) all quantitatively and selectively quenched the SN-CQDs’ native fluorescence, which was the base-for their-spectrofluorimetric estimation without the need for any tedious pre-treatment steps or high-cost instrumentation. SN-CQDs demonstrated a “turn-off” fluorescence response to RFP, TNZ, ONZ, and MNZ over the ranges of 1.0–30.0, 10.0–200.0, 6.0–200.0, and 5.0–100.0 μM with detection limits of 0.31, 1.76, 0.57, and 0.75 μM and quantitation limits of 0.93, 5.32, 1.74, and 2.28 μM respectively. The suggested method was successfully used to determine the investigated drugs in their commercial dosage forms. The method was further extended to their determination in spiked human plasma samples, with satisfactory mean % recoveries (99.44–100.29) and low % RSD values (< 4.52). The mechanism of fluorescence quenching was studied and discussed. The suggested method was validated in accordance with ICH recommendations.
Self-report symptom-based endometriosis prediction using machine learning
Authors: Goldstein Anat , Cohen Shani 
Published: April 2023

AbstractEndometriosis is a chronic gynecological condition that affects 5–10% of reproductive age women. Nonetheless, the average time-to-diagnosis is usually between 6 and 10 years from the onset of symptoms. To shorten time-to-diagnosis, many studies have developed non-invasive screening tools. However, most of these studies have focused on data obtained from women who had/were planned for laparoscopy surgery, that is, women who were near the end of the diagnostic process. In contrast, our study aimed to develop a self-diagnostic tool that predicts the likelihood of endometriosis based only on experienced symptoms, which can be used in early stages of symptom onset. We applied machine learning to train endometriosis prediction models on data obtained via questionnaires from two groups of women: women who were diagnosed with endometriosis and women who were not diagnosed. The best performing model had AUC of 0.94, sensitivity of 0.93, and specificity of 0.95. The model is intended to be incorporated into a website as a self-diagnostic tool and is expected to shorten time-to-diagnosis by referring women with a high likelihood of having endometriosis to further examination. We also report the importance and effectiveness of different symptoms in predicting endometriosis.
Structure-preserving visualization for single-cell RNA-Seq profiles using deep manifold transformation with batch-correction
Authors: Xu Yongjie , Zang Zelin , Xia Jun , Tan Cheng , Geng Yulan , Li Stan Z. 
Published: April 2023

AbstractDimensionality reduction and visualization play an important role in biological data analysis, such as data interpretation of single-cell RNA sequences (scRNA-seq). It is desired to have a visualization method that can not only be applicable to various application scenarios, including cell clustering and trajectory inference, but also satisfy a variety of technical requirements, especially the ability to preserve inherent structure of data and handle with batch effects. However, no existing methods can accommodate these requirements in a unified framework. In this paper, we propose a general visualization method, deep visualization (DV), that possesses the ability to preserve inherent structure of data and handle batch effects and is applicable to a variety of datasets from different application domains and dataset scales. The method embeds a given dataset into a 2- or 3-dimensional visualization space, with either a Euclidean or hyperbolic metric depending on a specified task type with type static (at a time point) or dynamic (at a sequence of time points) scRNA-seq data, respectively. Specifically, DV learns a structure graph to describe the relationships between data samples, transforms the data into visualization space while preserving the geometric structure of the data and correcting batch effects in an end-to-end manner. The experimental results on nine datasets in complex tissue from human patients or animal development demonstrate the competitiveness of DV in discovering complex cellular relations, uncovering temporal trajectories, and addressing complex batch factors. We also provide a preliminary attempt to pre-train a DV model for visualization of new incoming data.
Maternal glucagon-like peptide-1 is positively associated with fetal growth in pregnancies complicated with obesity
Authors: Dumolt Jerad H. , Rosario Fredrick J. , Kramer Avery C. , Horwitz Stacee , Powell Theresa L. , Jansson Thomas 
Published: April 2023

Abstract
Pregnant women with obesity are more likely to deliver infants who are large for gestational age (LGA). LGA is associated with increased perinatal morbidity and risk of developing metabolic disease later in life. However, the mechanisms underpinning fetal overgrowth remain to be fully established. Here, we identified maternal, placental, and fetal factors that are associated with fetal overgrowth in pregnant women with obesity. Maternal and umbilical cord plasma and placentas were collected from women with obesity delivering infants who were LGA (n=30) or appropriate for gestational age (AGA, n=21) at term. Maternal and umbilical cord plasma analytes were measured using multiplex sandwich assay and ELISA. Insulin/mechanistic target of rapamycin (mTOR) signaling activity was determined in placental homogenates. Amino acid transporter activity was measured in isolated syncytiotrophoblast microvillous membrane (MVM) and basal membrane (BM). Glucagon-like peptide-1 receptor (GLP-1R) protein expression and signaling were measured in cultured primary human trophoblast (PHT) cells. Maternal plasma glucagon-like peptide-1 (GLP-1) was higher in LGA pregnancies and positively correlated to birthweight. Umbilical cord plasma insulin, C-peptide, and GLP-1 were increased in obese-large for gestational age (OB-LGA) infants. LGA placentas were larger but showed no change in insulin/mTOR signaling or amino acid transport activity. GLP-1R protein was expressed in the MVM isolated from human placenta. GLP-1R activation stimulated protein kinase alpha (PKA), extracellular signal-regulated kinase-1 and-2 (ERK1/2), and mTOR pathways in PHT cells. Our results suggest elevated maternal GLP-1 may drive fetal overgrowth in obese pregnant women. We speculate that maternal GLP-1 acts as a novel regulator of fetal growth by promoting placental growth and function.
Malignant melanoma dermoscopy image classification method based on multi‐modal medical features
Authors: Bian Xiaofei , Pan Haiwei , Zhang Kejia , Liu Peng , Chen Chunling 
Published: April 2023

AbstractSkin cancer is one of the deadliest cancers, and it has been widely developed worldwide since the last decade. Malignant melanoma is currently the most deadly skin cancer. If malignant melanoma is diagnosed at an early stage, the probability of patients being cured will be greatly improved. At present, most existing skin lesion image classification methods only use deep learning. However, the multi‐modal features of skin lesions in the medical domain are not well utilized and integrated. To reduce the classification error of the skin lesion images caused by the complexity and subjectivity of visual interpretation, a malignant melanoma dermoscopy image classification method based on multi‐modal medical features is proposed in this paper which is inspired by the fuzzy decision‐making process of doctors. It can reduce the subjective difference in the image classification process and assist dermatologists to analyze the skin lesion area. Firstly, the feature detection method based on the extension theory can effectively quantify the difference between different colour features. Then, an interpretable segmentation edge of the skin lesion is established by using the neutrosophic theory which can convert the image into the neutrosophic space. The edge of the skin lesion is captured by applying the Hierarchical Gaussian Mixture Model (HGMM) method. Next, the edge sequence is established by segmenting the edge, and the contour regularity, symmetry, and uniformity of the edge of the skin lesion are analyzed. Finally, the extracted multi‐feature sets are used for dermoscopy image classification. Experiments are carried out on real datasets, and the classification accuracy of four kernel functions is verified. The experimental results show that the authors’ method can effectively improve the classification accuracy of benign dermoscopy images and malignant dermoscopy images.
Suppression of dc‐offset current in ac‐link of dual‐active‐bridge dc‐dc converter based on triple‐phase‐shift optimal control
Authors: Ren Qiang , Ai Sheng , Kang Wei , Jiang Yapeng 
Published: April 2023

AbstractWhen dual‐active‐bridge dc‐dc converter (DAB) with energy storage load operates in a wide voltage range and high dynamic condition, the mismatch of primary and secondary side voltages will lead to high current stress and loss, and the dc‐offset current in the high‐frequency ac link will lead to magnetic saturation of magnetic components, which will damage the devices in serious cases. Therefore, aiming at the operation of DAB in a wide voltage range, a triple‐phase‐shift (TPS) optimal control strategy is adopted, and the phase shift angles of the bridges are adjusted according to the voltage ratio, so as to optimize the electrical stress and loss. What is more, the cause and mechanism of dc‐offset current in the ac‐link are analysed. Based on the TPS optimal strategy, the static dc‐offset current is suppressed with the low‐bandwidth detection of the offset current and the dynamic dc‐offset current is suppressed with the planning the current trajectory. A small‐power prototype is built, and the effectiveness of the TPS optimal control and the static and dynamic dc‐offset current suppression is verified.
Dynamic and Polarimetric VLBI imaging with a multiscalar approach
Authors: Müller H. , Lobanov A. P. 
Published: April 2023

Context. Due to the limited number of antennas and the limited observation time, an array of antennas in very long baseline interfer-ometry (VLBI) often samples the Fourier domain only very sparsely. Powerful deconvolution algorithms are needed to compute a final image. Multiscale imaging approaches such as DoG-HiT have recently been developed to solve the VLBI imaging problem and show promising performance: they are fast, accurate, unbiased, and automatic.
Aims. We extend the multiscalar imaging approach to polarimetric imaging, to reconstructions of dynamically evolving sources, and finally to dynamic polarimetric reconstructions.
Methods. These extensions (mr-support imaging) utilize a multiscalar approach. The time-averaged Stokes I image was decomposed by a wavelet transform into single subbands. We used the set of statistically significant wavelet coefficients, the multiresolution support (mr-support), computed by DoG-HiT as a prior in a constrained minimization manner; we fitted the single-frame (polarimetric) observables by only varying the coefficients in the multiresolution support.
Results. The Event Horizon Telescope (EHT) is a VLBI array imaging supermassive black holes. We demonstrate on synthetic data that mr-support imaging offers ample regularization and is able to recover simple geometric dynamics at the horizon scale in a typical EHT setup. The approach is relatively lightweight, fast, and largely automatic and data driven. The ngEHT is a planned extension of the EHT designed to recover movies at the event horizon scales of a supermassive black hole. We benchmark the performance of mr-support imaging for the denser ngEHT configuration demonstrating the major improvements the additional ngEHT antennas will bring to dynamic polarimetric reconstructions.
Conclusions. Current and upcoming instruments offer the observational possibility to do polarimetric imaging of dynamically evolving structural patterns with the highest spatial and temporal resolution. State-of-the-art dynamic reconstruction methods can capture this motion with a range of temporal regularizers and priors. With this work, we add an additional simpler regularizer to the list: constraining the reconstruction to the multiresolution support.
Interaction of solar inertial modes with turbulent convection
Authors: Philidet J. , Gizon L. 
Published: April 2023

Context. Inertial modes have been observed on the Sun at low longitudinal wavenumbers. These modes probe the dynamics and structure of the solar convective zone down to the tachocline. While linear analysis allows the complex eigenfrequencies and eigenfunctions of these modes to be computed, it gives no information about their excitation nor about their amplitudes.
Aims. We tested the hypothesis that solar inertial modes are stochastically excited by the turbulent motions entailed by convection. Unlike the acoustic modes, which are excited by vertical turbulent motions, the inertial modes are excited by the radial vorticity of the turbulent field.
Methods. We have developed a theoretical formalism where the turbulent velocity fluctuations provide the mechanical work necessary to excite the modes. The modes are described by means of a 2D linear wave equation with a source term, under the β plane approximation. This wave equation restrained to a spherical surface is relevant for the quasi-toroidal inertial modes that are observed on the Sun. Latitudinal differential rotation is included in the form of a parabolic profile that approximates the solar differential rotation at low and mid latitudes. The turbulent vorticity field underlying the source term is treated as an input to the model and is constrained by observations of the solar surface. The solution to the linear inhomogeneous wave equation is written in terms of a Green function, which is computed numerically.
Results. We obtain synthetic power spectra for the wave’s latitudinal velocity, longitudinal velocity, and radial vorticity, with azimuthal orders between 1 and 20. The synthetic power spectra contain the classical equatorial Rossby modes, as well as a rich spectrum of additional modes. The mode amplitudes are found to be of the same order of magnitude as observed on the Sun (∼1 m s−1). There is a qualitative transition between low and high azimuthal orders: the power spectra for m ≲ 5 show modes that are clearly resolved in frequency space, while the power spectra for m ≳ 5 display regions of excess power that consist of many overlapping modes.
Conclusions. The general agreement between the predicted and observed inertial mode amplitudes supports the assumption of stochastic excitation by turbulent convection. Our work shows that the power spectra are not easily separable into individual modes, thus complicating the interpretation of the observations.
Statistical study of type III bursts and associated HXR emissions
Authors: James Tomin , Vilmer Nicole 
Published: April 2023

Context. Flare-accelerated electrons may produce closely temporarily related hard X-ray (HXR) emission while interacting with the dense solar atmosphere and radio type III bursts when propagating from the low corona to the interplanetary medium. The link between these emissions has been studied in previous studies. We present here new results on the correlation between the number and spectrum of HXR-producing electrons and the type III characteristics (flux, starting frequency).
Aims. The aim of this study is to extend the results from previous statistical studies of radio type III bursts and associated HXR emissions: in particular, to determine what kind of correlation, if any, exists between the HXR-emitting electron numbers and the radio flux, as well as whether any correlations between the electron numbers or energy spectra are deduced from associated HXR emissions and type III starting (stopping) frequencies.
Methods. This study is based on thirteen years of data between 2002 and 2014. We shortlisted ≃200 events with a close temporal association between HXR emissions and radio type III bursts in the 450–150 MHz range. We used X-ray flare observations from RHESSI and Fermi/GBM to calculate the number of electrons giving rise to the observed X-ray flux and observations from the Nançay Radioheliograph to calculate the peak radio flux at different frequencies in the 450–150 MHz range. Under the assumption of thick-target emissions, the number of HXR-producing electrons and their energy spectra were computed. The correlation between electron numbers, power-law indices, and the peak radio fluxes at different frequencies were analysed as well as potential correlations between the electron numbers and starting frequency of the radio burst. Bootstrap analysis for the correlation coefficients was performed to quantify the statistical significance of the fit.
Results. The correlation between the number of HXR electrons and the peak flux of the type III emission decreases with increasing frequency. This correlation is larger when considering the electron number above 20 keV rather than the electron number above 10 keV. A weak anti-correlation is also found between the absolute value of the electron spectral index and the peak radio flux at 228 MHz. A rough correlation is found between the HXR-producing electron number above 20 keV and the type III starting frequency. This correlation is smaller if the electron number above 10 keV is considered. All the results are discussed in the framework of results from previous studies and in the context of numerical simulations of bump-in-tail instabilities and subsequent radio emissions.