bluuebunny/crossref_metadata_2025_split huggingface dataset:
MXene/graphene oxide nanocomposites for friction and wear reduction of rough steel surfaces
Authors: Macknojia Ali Zayaan , Ayyagari Aditya , Shevchenko Elena , Berman Diana 
Published: July 2023

AbstractDevelopment of solid lubricant materials that render reliable performance in ambient conditions, are amenable to industrial size and design complexities, and work on engineered surfaces is reported. These coatings are composed of Ti3C2Tx-Graphene Oxide blends, spray-coated onto bearing steel surfaces. The tribological assessment was carried out in ambient environmental conditions and high contact pressures in a ball-on-disc experimental set-up. The evaluation yielded that the use of Ti3C2Tx-Graphene-Oxide coatings led to substantial reduction in friction down to 0.065 (at 1 GPa contact pressure and 100 mm/s) in comparison to the uncoated of single-component-coated surfaces, surpassing the state-of-the-art. The coatings also provided excellent protection against wear loss of the substrate and counter-face. The results were explained based on the observations from Raman spectroscopy, scanning electron microscopy, transmission electron microscopy, and nanoindentation measurements. In operando formation of a dense, hard and stiff, dangling-bond-saturated tribolayer was observed to be the reason for the sustained lubricity even at high test loads and sliding speeds. This report presents the holistic exploration and correlation of structure-property-processing pertaining to the advancement of solid lubrication science.
Rapid screening of SARS-CoV-2 variants, a key tool for pandemic surveillance
Authors: Muñoz-Gallego Irene , Meléndez Carmona María Ángeles , Martín Higuera Carmen , Viedma Esther , Delgado Rafael , Folgueira María Dolores 
Published: July 2023

AbstractThe utility of reverse transcription-polymerase chain reaction (RT-PCR) in analysis SARS-COV-2 variants was evaluated. RT-PCR tests were used to analyse the majority of new SARS-CoV-2 cases (n = 9315) in a tertiary hospital (Madrid, Spain) throughout 2021. Subsequently, whole genome sequencing (WGS) was conducted on 10.8% of these samples (n = 1002). Notably, the Delta and Omicron variants emerged rapidly. There were no discrepancies between RT-PCR and WGS results. Continuous surveillance of SARS-CoV-2 variants is essential, and RT-PCR is a highly useful method, specially during periods of high COVID-19 incidence. This feasible technique can be implemented in all SARS-CoV-2 laboratories. However, WGS remains the gold standard method for comprehensive detection of all existing SARS-CoV-2 variants.
Potential use of dry powder of Vossia cuspidata (Roxb.) Griff. rhizomes and leaves in methylene blue dye remediation
Authors: Awad Hossam E. A. , Mohammad Ahmad M. , Farahat Emad A. 
Published: July 2023

AbstractPhytoremediation is a promising, cost-effective, and eco-friendly process for wastewater treatment. Herein, the dry biomasses of Vossia cuspidata (Roxb.) Griff. leaves (PL) and rhizomes including aerial stems (PR) were used to effectively remediate methylene blue (MB) dyes. Interestingly, the adsorption uptake and removal efficiency of MB by PR were higher than those of PL; exceeding 97 and 91% in 35 and 25 min for 0.1 and 0.4 g/L MB, respectively. The MB diffusion within the PL and PR was insignificant and the adsorption kinetics was principally controlled by the surface MB–adsorbent interaction, as consistently approved by the pseudo-second order kinetic model. In addition, the adsorption increased rapidly with the plant dosage with high dependence on the initial MB concentration. Moreover, the impact of shaking speed on the adsorption was minor but temperature played a critical role where the highest efficiencies were recorded at 30 and 40 °C on PL (91.9%) and PR (93.3%), respectively. The best removal efficiencies were attained with PR at pH 6, but with PL at pH 8. The Temkin isotherm could perfectly simulate the experimental data (R2 > 0.97); suggesting a linear decrease of the adsorption heat of MB with the plant coverage.
Dog ownership may promote cardiometabolic health in U.S. military veterans
Authors: Woodward Steven H. , Baldassarri Stephen R. , Pietrzak Robert H. 
Published: July 2023

AbstractDog ownership has been associated with reduced cardiovascular and all-cause mortality in civilian epidemiological samples. Associations between dog ownership and cardiometabolic disease were examined in the 2019–2020 wave of the National Health and Resilience in Veterans Study. Dog and cat ownership data were obtained from 3078 Veterans and cross-tabulated with self-reported, professionally diagnosed, heart disease, heart attack, stroke, high blood pressure, diabetes, and high cholesterol. In unadjusted tests, dog ownership was associated with lower rates of heart disease, high blood pressure, diabetes, and high cholesterol, while cat ownership was not. Relative to non-owners, dog owners were younger, were more likely to screen positive for posttraumatic stress disorder and/or major depressive disorder, and more active. Binary logistic regression models of associations between dog ownership and cardiometabolic disease were adjusted for age, sex, trauma load, mood disorder, substance abuse, nicotine abuse, and exercise. After adjustment, dog ownership was still associated with lower odds of hypertension and high cholesterol. Dog ownership also interacted with exercise to lower odds of heart disease and attenuated the effect of trauma load on hypertension. Conversely, age interacted with dog ownership such that odds of diabetes and stroke were higher in older Veterans who owned dogs.
Aluminum surface defect detection method based on a lightweight YOLOv4 network
Authors: Li Songsong , Guo Shangrong , Han Zhaolong , Kou Chen , Huang Benchi , Luan Minghui 
Published: July 2023

AbstractDeep learning is currently being used to automate surface defect detection in aluminum. The common target detection models based on neural networks often have a large number of parameters and a slow detection speed, which is not conducive to real-time detection. Therefore, this paper proposes a lightweight aluminum surface defect detection model, M2-BL-YOLOv4, based on the YOLOv4 algorithm. First, in the YOLOv4 model, the complex CSPDarkNet53 backbone network was modified into an inverted residual structure, which greatly reduced the number of parameters in the model and increased the detection speed. Second, a new feature fusion network, BiFPN-Lite, is designed to improve the fusion ability of the network and further improve its detection accuracy. The final results show that the mean average precision of the improved lightweight YOLOv4 algorithm in the aluminum surface defect test set reaches 93.5%, the number of model parameters is reduced to 60% of the original, and the number of frames per second (FPS) detected is 52.99, which increases the detection speed by 30%. The efficient detection of aluminum surface defects is realized.
Serum RGC-32 in children with systemic lupus erythematosus
Authors: Huang Bingxue , Feng Dan , Niu Xiaoling , Huang Wenyan , Hao Sheng 
Published: July 2023

AbstractChildhood-onset systemic lupus erythematosus (SLE) can be more severe than adult patients. Early diagnosis and accurate evaluation of the disease are very important for the patients. Response gene to complement-32 (RGC-32) protein is the downstream regulator of C5b-9 complex which is the terminal pathway of complement activation. Complement system plays a very important role in the pathogenesis of SLE. RGC-32 in patients with SLE has not been reported yet. We aimed to examine the clinical value of RGC-32 in children with SLE. A total of 40 children with SLE and another 40 healthy children were enrolled for this study. Clinical data were obtained prospectively. Serum RGC-32 was determined by ELISA. We found that serum RGC-32 was significantly elevated in children with SLE than that in the healthy group. Serum RGC-32 was significantly higher in the children with moderately/severely active SLE than that in the children with no/mildly active SLE. Furthermore, serum RGC-32 level correlated positively with C-reactive protein, erythrocyte sedimentation rate and ferritin and correlated negatively with white blood cell counts and C3. RGC-32 may be involved in the pathogenesis of SLE. RGC-32 might become a good biomarker in the diagnosis and evaluation of SLE.
Bias sputtering of granular L10-FePt films with hexagonal boron nitride grain boundaries
Authors: Xu Chengchao , Varaprasad B. S. D. Ch. S. , Laughlin David E. , Zhu Jian-Gang 
Published: July 2023

AbstractIn this paper, we present an experimental study of L10-FePt granular films with crystalline boron nitride (BN) grain boundary materials for heat assisted magnetic recording (HAMR). It is found that application of a RF substrate bias (VDC = -15 V) yields the formation of hexagonal boron nitride (h-BN) nanosheets in grain boundaries, facilitating the columnar growth of FePt grains during sputtering at high temperatures. The h-BN monolayers conform to the side surfaces of columnar FePt grains, completely encircling individual FePt grains. The resulting core–shell FePt-(h-BN) nanostructures appear to be highly promising for HAMR application. The high thermal stability of h-BN grain boundaries allows the deposition temperature to be as high as 650℃ such that high order parameters of FePt L10 phase have been obtained. For the fabricated FePt-(h-BN) thin film, excellent granular microstructure with FePt grains of 6.5 nm in diameter and 11.5 nm in height has been achieved along with good magnetic hysteresis properties.
Prediction of habitat complexity using a trait-based approach on coral reefs in Guam
Authors: Ferreira Sofia B. , Burns John H. R. , Pascoe Kailey H. , Kapono Clifford A. , Reyes Andres J. , Fukunaga Atsuko 
Published: July 2023

AbstractScleractinian corals are primary contributors to the structural complexity of coral reef ecosystems. The structure derived from their carbonate skeletons underpins the biodiversity and myriad of ecosystem services provided by coral reefs. This study used a trait-based approach to provide new insights into the relationships between habitat complexity and coral morphology. Three-Dimensional (3D) photogrammetry techniques were used to survey 208 study plots on the island of Guam, from which structural complexity metrics were derived and physical traits of corals were quantified. Three traits at the individual colony level (e.g., morphology, size, and genera) and two site-level environmental characteristics (e.g., wave exposure and substratum-habitat type) were examined. Standard taxonomy-based metrics were also included at the reef-plot level (e.g., coral abundance, richness, and diversity). Different traits disproportionately contributed to 3D metrics of habitat complexity. Larger colonies with a columnar morphology have the highest contribution to surface complexity, slope, and vector ruggedness measure, whereas branching and encrusting columnar colonies have the highest contribution to planform and profile curvature. These results highlight the importance of considering colony morphology and size in addition to conventional taxonomic metrics for the understanding and monitoring reef structural complexity. The approach presented here provides a framework for studies in other locations to predict the trajectory of reefs under changing environmental conditions.
Targeted metabolomic profiling as a tool for diagnostics of patients with non-small-cell lung cancer
Authors: Shestakova Ksenia M. , Moskaleva Natalia E. , Boldin Andrey A. , Rezvanov Pavel M. , Shestopalov Alexandr V. , Rumyantsev Sergey A. , Zlatnik Elena Yu. , Novikova Inna A. , Sagakyants Alexander B. , Timofeeva Sofya V. , Simonov Yuriy , Baskhanova Sabina N. , Tobolkina Elena , Rudaz Serge , Appolonova Svetlana A. 
Published: July 2023

AbstractLung cancer is referred to as the second most common cancer worldwide and is mainly associated with complex diagnostics and the absence of personalized therapy. Metabolomics may provide significant insights into the improvement of lung cancer diagnostics through identification of the specific biomarkers or biomarker panels that characterize the pathological state of the patient. We performed targeted metabolomic profiling of plasma samples from individuals with non-small cell lung cancer (NSLC, n = 100) and individuals without any cancer or chronic pathologies (n = 100) to identify the relationship between plasma endogenous metabolites and NSLC by means of modern comprehensive bioinformatics tools, including univariate analysis, multivariate analysis, partial correlation network analysis and machine learning. Through the comparison of metabolomic profiles of patients with NSCLC and noncancer individuals, we identified significant alterations in the concentration levels of metabolites mainly related to tryptophan metabolism, the TCA cycle, the urea cycle and lipid metabolism. Additionally, partial correlation network analysis revealed new ratios of the metabolites that significantly distinguished the considered groups of participants. Using the identified significantly altered metabolites and their ratios, we developed a machine learning classification model with an ROC AUC value equal to 0.96. The developed machine learning lung cancer model may serve as a prototype of the approach for the in-time diagnostics of lung cancer that in the future may be introduced in routine clinical use. Overall, we have demonstrated that the combination of metabolomics and up-to-date bioinformatics can be used as a potential tool for proper diagnostics of patients with NSCLC.
Synthesis and pharmacological activity of the epimers of hexahydrocannabinol (HHC)
Authors: Russo Fabiana , Vandelli Maria Angela , Biagini Giuseppe , Schmid Martin , Luongo Livio , Perrone Michela , Ricciardi Federica , Maione Sabatino , Laganà Aldo , Capriotti Anna Laura , Gallo Alfonso , Carbone Luigi , Perrone Elisabetta , Gigli Giuseppe , Cannazza Giuseppe , Citti Cinzia 
Published: July 2023

AbstractCannabis is a multifaceted plant with numerous therapeutic properties on one hand, and controversial psychotropic activities on the other hand, which are modulated by CB1 endocannabinoid receptors. Δ9-Tetrahydrocannabinol (Δ9-THC) has been identified as the main component responsible for the psychotropic effects, while its constitutional isomer cannabidiol (CBD) has shown completely different pharmacological properties. Due to its reported beneficial effects, Cannabis has gained global popularity and is openly sold in shops and online. To circumvent legal restrictions, semi-synthetic derivatives of CBD are now frequently added to cannabis products, producing "high" effects similar to those induced by Δ9-THC. The first semi-synthetic cannabinoid to appear in the EU was obtained through cyclization and hydrogenation of CBD, and is known as hexahydrocannabinol (HHC). Currently, there is limited knowledge regarding HHC, its pharmacological properties, and its prevalence, as it is not commonly investigated in routine toxicological assays. In this study, synthetic strategies were explored to obtain an excess of the active epimer of HHC. Furthermore, the two epimers were purified and individually tested for their cannabinomimetic activity. Lastly, a simple and rapid chromatographic method employing a UV detector and a high-resolution mass spectrometer was applied to identify and quantify up to ten major phytocannabinoids, as well as the HHC epimers, in commercial cannabis samples.
Stressed neuronal cells can recover from profound membrane blebbing, nuclear condensation and mitochondrial fragmentation, but not from cytochrome c release
Authors: You Wenting , Zhou Tao , Knoops Kèvin , Berendschot Tos T. J. M. , van Zandvoort Marc A. M. J. , Germeraad Wilfred T. V. , Benedikter Birke , Webers Carroll A. B. , Reutelingsperger Chris P. M. , Gorgels Theo G. M. F. 
Published: July 2023

AbstractLoss of neurons in chronic neurodegenerative diseases may occur over a period of many years. Once initiated, neuronal cell death is accompanied by distinct phenotypic changes including cell shrinkage, neurite retraction, mitochondrial fragmentation, nuclear condensation, membrane blebbing and phosphatidylserine (PS) exposure at the plasma membrane. It is still poorly understood which events mark the point of no return for dying neurons. Here we analyzed the neuronal cell line SH-SY5Y expressing cytochrome C (Cyto.C)-GFP. Cells were exposed temporarily to ethanol (EtOH) and tracked longitudinally in time by light and fluorescent microscopy. Exposure to EtOH induced elevation of intracellular Ca2+ and reactive oxygen species, cell shrinkage, neurite retraction, mitochondrial fragmentation, nuclear condensation, membrane blebbing, PS exposure and Cyto.C release into the cytosol. Removing EtOH at predetermined time points revealed that all phenomena except Cyto.C release occurred in a phase of neuronal cell death in which full recovery to a neurite-bearing cell was still possible. Our findings underscore a strategy of treating chronic neurodegenerative diseases by removing stressors from neurons and harnessing intracellular targets that delay or prevent trespassing the point of no return.
Bound entanglement is not Lorentz invariant
Authors: Caban Paweł , Hiesmayr Beatrix C. 
Published: July 2023

AbstractBound entanglement, in contrast to free entanglement, cannot be distilled into maximally entangled states by two local observers applying measurements and utilizing classical communication. In this paper we ask whether a relativistic observer classifies states according to being separable, bound or free entangled in the same manner as an unboosted observer. Surprisingly, this turns out not to be the case. And that even if the system in a given inertial frame of reference is separable with respect to the partition momenta versus spins. In detail, we show that if the spin state is initially bound entangled, some boosted observers observe their spin states to be either bound entangled, separable or free entangled. This also explains why a general measure of the entanglement property is difficult to find.
Quantification of cartilage and subchondral bone cysts on knee specimens based on a spectral photon-counting computed tomography
Authors: Garcelon Célestin , Abascal Juan , Olivier Cecile , Uk Stéphanie , Si-Mohamed Salim , Ea Hang-Korng , Douek Philippe , Peyrin Francoise , Chappard Christine 
Published: July 2023

AbstractSpectral photon-counting computed tomography (SPCCT) is a new technique with the capability to provide mono-energetic (monoE) images with high signal to noise ratio. We demonstrate the feasibility of SPCCT to characterize at the same time cartilage and subchondral bone cysts (SBCs) without contrast agent in osteoarthritis (OA). To achieve this goal, 10 human knee specimens (6 normal and 4 with OA) were imaged with a clinical prototype SPCCT. The monoE images at 60 keV with isotropic voxels of 250 × 250 × 250 µm3 were compared with monoE synchrotron radiation CT (SR micro-CT) images at 55 keV with isotropic voxels of 45 × 45 × 45 µm3 used as benchmark for cartilage segmentation. In the two OA knees with SBCs, the volume and density of SBCs were evaluated in SPCCT images. In 25 compartments (lateral tibial (LT), medial tibial, (MT), lateral femoral (LF), medial femoral and patella), the mean bias between SPCCT and SR micro-CT analyses were 101 ± 272 mm3 for cartilage volume and 0.33 mm ± 0.18 for mean cartilage thickness. Between normal and OA knees, mean cartilage thicknesses were found statistically different (0.005 < p < 0.04) for LT, MT and LF compartments. The 2 OA knees displayed different SBCs profiles in terms of volume, density, and distribution according to size and location. SPCCT with fast acquisitions is able to characterize cartilage morphology and SBCs. SPCCT can be used potentially as a new tool in clinical studies in OA.
A comparison of different machine-learning techniques for the selection of a panel of metabolites allowing early detection of brain tumors
Authors: Godlewski Adrian , Czajkowski Marcin , Mojsak Patrycja , Pienkowski Tomasz , Gosk Wioleta , Lyson Tomasz , Mariak Zenon , Reszec Joanna , Kondraciuk Marcin , Kaminski Karol , Kretowski Marek , Moniuszko Marcin , Kretowski Adam , Ciborowski Michal 
Published: July 2023

AbstractMetabolomics combined with machine learning methods (MLMs), is a powerful tool for searching novel diagnostic panels. This study was intended to use targeted plasma metabolomics and advanced MLMs to develop strategies for diagnosing brain tumors. Measurement of 188 metabolites was performed on plasma samples collected from 95 patients with gliomas (grade I–IV), 70 with meningioma, and 71 healthy individuals as a control group. Four predictive models to diagnose glioma were prepared using 10 MLMs and a conventional approach. Based on the cross-validation results of the created models, the F1-scores were calculated, then obtained values were compared. Subsequently, the best algorithm was applied to perform five comparisons involving gliomas, meningiomas, and controls. The best results were obtained using the newly developed hybrid evolutionary heterogeneous decision tree (EvoHDTree) algorithm, which was validated using Leave-One-Out Cross-Validation, resulting in an F1-score for all comparisons in the range of 0.476–0.948 and the area under the ROC curves ranging from 0.660 to 0.873. Brain tumor diagnostic panels were constructed with unique metabolites, which reduces the likelihood of misdiagnosis. This study proposes a novel interdisciplinary method for brain tumor diagnosis based on metabolomics and EvoHDTree, exhibiting significant predictive coefficients.
A stratified flow of a non-Newtonian Casson fluid comprising microorganisms on a stretching sheet with activation energy
Authors: Lone Showkat Ahmad , Anwar Sadia , Saeed Anwar , Bognár Gabriella 
Published: July 2023

AbstractA stratified flow may be seen regularly in a number of significant industrial operations. For instance, the stratified flow regime is typically used by gas-condensate pipelines. Clearly, only a limited set of working situations for which this flow arrangement is stable allow for the achievement of the stratified two-phase flow zone. In this paper, the authors are considered the laminar, steady and incompressible magnetohydrodynamic flow of a non-Newtonian Casson fluid flow past a stratified extending sheet. The features of bio-convection, Brownian motion, thermal radiation thermophoresis, heat source, and chemically reactive activation energy have been employed. The set of equations administered flow of fluid is converted into ordinary differential equation by suitable variables. A semi-analytical investigation of the present analysis is performed with homotopy analysis method. Endorsement of the current results with previous results is also investigated. The outcomes showed that the velocity distribution of the fluid flow lessens with higher Casson and magnetic factors. The temperature profiles of fluid flow shrinkage as the Prandtl number and Casson factor increase and enlarges with higher values of thermal radiation, magnetic, and Brownian motion factors. It is found that the growing thermophoretic and Brownian motion factors reduce the rate of thermal flow of the Casson fluid flow. In contrast, the increasing thermal stratification parameter increases the thermal flow rate of fluid.