54,391 research outputs found

    Table1_Silicon and gadolinium co-doped hydroxyapatite/PLGA scaffolds with osteoinductive and MRI dual functions.DOCX

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    Introduction: An ideal bone repair scaffold should have dual functions of osteoinductive ability and in vivo imaging. In this study, the simultaneous substitution of silicon (Si) and gadolinium (Gd) in hydroxyapatite (HA) as potential multifunctional bone graft materials has been successfully developed.Methods: A series of HA nanoparticles (HA NPs) doped with different proportions of Si and Gd were prepared. The chemical structure and phase composition of the materials were analyzed using Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD). The microstructure, magnetic properties, surface potential, and cytotoxicity of the materials were also analyzed. The magnetic resonance imaging (MRI) effect of Gd&Si-HA/poly(lactic-co-glycolic acid) (Gd&Si-HA/PLGA) composite materials was evaluated. Osteogenic-related gene expression, alkaline phosphatase (ALP) level, and mineralization capacity of MC3T3-E1 cultured on Gd&Si-HA/PLGA composite materials were also detected.Results and Discussion: The 1.5Gd&Si-HA@PLGA group showed good ability to promote osteogenic differentiation of cells. The MRI effect of the 1.5Gd&Si-HA@PLGA scaffold was observable. This HA material containing Si and Gd co-doping has a broad application prospect in the field of bone tissue engineering owing to its ability to enhance osteoinductive property and improve MRI effect.</p

    Additional file 1 of Chronic restraint stress promotes oral squamous cell carcinoma development by inhibiting ALDH3A1 via stress response hormone

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    Additional file 1: Supplementary Materials and Methods. Supplementary Table 1. Primer sequences for qPCR amplification of specific genes. Supplementary Figure 1. Immunofluorescent staining of EMT-related markers in OSCC cells with Con and NE groups. Supplementary Figure 2. Immunofluorescent staining of EMT-related markers in OSCC cells with NE+Lv-Con and NE+Lv-ALDH3A1 groups. Supplementary Figure 3. Relative levels of ATP production and OCR of Lv-Con and Lv-ALDH3A1 HN6 and HSC4 without NE treatment. Supplementary of figure 2g. The original pictures of western blots of figure 2g. Supplementary of figure 3d. The original pictures of western blots of Figure 3d. Supplementary of figure 3f. The original pictures of western blots of Figure 3f. Supplementary of figure 4f. The original pictures of western blots of Figure 4f

    sj-png-2-tar-10.1177_17534666231223002 – Supplemental material for A simple and efficient clinical prediction scoring system to identify malignant pleural effusion

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    Supplemental material, sj-png-2-tar-10.1177_17534666231223002 for A simple and efficient clinical prediction scoring system to identify malignant pleural effusion by Shuyan Wang, Jing An, Xueru Hu, Tingting Zeng, Ping Li, Jiangyue Qin, Yongchun Shen, Tao Wang and Fuqiang Wen in Therapeutic Advances in Respiratory Disease</p

    Sesquiterpenes from <i>Wikstroemia lungtzeensis</i> with anti-neuroinflammatory effects

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    An anti-neuroinflammatory activities-guided phytochemical research of Wikstroemia lungtzeensis was performed for the first time. Three undescribed carotane-type sesquiterpenes, excoecafolinols C-E (1–3), and nine known sesquiterpene derivatives were isolated from the effective ethyl acetate extract of W. lungtzeensis. Their structures were determined based on multiple spectroscopic techniques and electronic circular dichroism (ECD) spectra. Furthermore, the anti-neuroinflammatory activities of the identified compounds were evaluated in lipopolysaccharide-stimulated BV-2 cells. Among them, six components (1, 2, 4, 7, 11, 12) exhibited significant inhibitory effects on nitric oxide (NO) production, with IC50 values ranging from 10.48 to 49.41 μM (positive control minocycline, IC50 53.20 μM). Carotane-type sesquiterpenes (1, 2, 4) with high content and significant inhibitory effects, are considered to be major active ingredients of W. lungtzeensis, which might serve as potential therapeutic agents for neurodegenerative diseases.</p

    Understanding District Heating Networks Vulnerability: A Comprehensive Analytical Approach with Controllability Consideration

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    International audienceDistrict heating networks (DHNs) are critical infrastructures that ensure production and residents' living. Analyzing vulnerability characteristics of DHNs is of great significance in heating safety decision-making. In this study, we analyze the structure, function, operation, and failure characteristics of DHNs and propose vulnerability analysis methods. We develop failure simulation models under fully-controllable (FC) and uncontrollable (UC) conditions for six failure scenarios based on component importance. To verify the proposed methods' effectiveness, we applied them to a DHN in a Chinese city. Upon analyzing the appositeness of various vulnerability assessment indicators, we find that the heat source connectivity efficiency loss rate, established based on hydraulic distribution in DHNs, can effectively characterize both topological and functional vulnerability. Our analysis also reveals that controllable DHNs, which evenly distribute heat supply among connected users for fairness, can result in lower flow and greater functional vulnerability compared to UC DHNs. In particular, under large area failure (AF) scenarios, the average functional vulnerability of UC DHNs increases by 27.59% to 38.30% compared to small-AF scenarios, while that of controllable DHNs increases by 103.78% to 120.58%. The proposed vulnerability assessment framework considering topology and function from both quantitative and qualitative perspectives, can grasp heating vulnerabilities multi-dimensional

    Supplementary data for "Whole Genome Duplication Events likely contributed to the Aquatic Adaptive Evolution of Parkerioideae"

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    Supplementary data for "Whole Genome Duplication Events likely contributed to the Aquatic Adaptive Evolution of Parkerioideae", Please find the details of each file in "0.read_me.txt".</p

    Multiplicity dependence of σψ(2S)/σJ/ψ\sigma_{\psi(2S)}/\sigma_{J/\psi} in pppp collisions at s=13\sqrt{s}=13 TeV

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    International audienceThe ratio of production cross-sections of ψ(2S)\psi(2S) over J/ψJ/\psi mesons as a function of charged-particle multiplicity in proton-proton collisions at a centre-of-mass energy s=13\sqrt{s}=13 TeV is measured with a data sample collected by the LHCb detector, corresponding to an integrated luminosity of 658 pb1^{-1}. The ratio is measured for both prompt and non-prompt ψ(2S)\psi(2S) and J/ψJ/\psi mesons. When there is an overlap between the rapidity ranges over which multiplicity and charmonia production are measured, a multiplicity-dependent modification of the ratio is observed for prompt mesons. No significant multiplicity dependence is found when the ranges do not overlap. For non-prompt production, the ψ(2S)toJ/ψ\psi(2S)-to-J/\psi production ratio is roughly independent of multiplicity irrespective of the rapidity range over which the multiplicity is measured. The results are compared to predictions of the co-mover model and agree well except in the low multiplicity region. The ratio of production cross-sections of ψ(2S)\psi(2S) over J/ψJ/\psi mesons are cross-checked with other measurements in di-lepton channels and found to be compatible

    Table_1_Development and validation of machine learning-augmented algorithm for insulin sensitivity assessment in the community and primary care settings: a population-based study in China.docx

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    ObjectiveInsulin plays a central role in the regulation of energy and glucose homeostasis, and insulin resistance (IR) is widely considered as the “common soil” of a cluster of cardiometabolic disorders. Assessment of insulin sensitivity is very important in preventing and treating IR-related disease. This study aims to develop and validate machine learning (ML)-augmented algorithms for insulin sensitivity assessment in the community and primary care settings.MethodsWe analyzed the data of 9358 participants over 40 years old who participated in the population-based cohort of the Hubei center of the REACTION study (Risk Evaluation of Cancers in Chinese Diabetic Individuals). Three non-ensemble algorithms and four ensemble algorithms were used to develop the models with 70 non-laboratory variables for the community and 87 (70 non-laboratory and 17 laboratory) variables for the primary care settings to screen the classifier of the state-of-the-art. The models with the best performance were further streamlined using top-ranked 5, 8, 10, 13, 15, and 20 features. Performances of these ML models were evaluated using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPR), and the Brier score. The Shapley additive explanation (SHAP) analysis was employed to evaluate the importance of features and interpret the models.ResultsThe LightGBM models developed for the community (AUROC 0.794, AUPR 0.575, Brier score 0.145) and primary care settings (AUROC 0.867, AUPR 0.705, Brier score 0.119) achieved higher performance than the models constructed by the other six algorithms. The streamlined LightGBM models for the community (AUROC 0.791, AUPR 0.563, Brier score 0.146) and primary care settings (AUROC 0.863, AUPR 0.692, Brier score 0.124) using the 20 top-ranked variables also showed excellent performance. SHAP analysis indicated that the top-ranked features included fasting plasma glucose (FPG), waist circumference (WC), body mass index (BMI), triglycerides (TG), gender, waist-to-height ratio (WHtR), the number of daughters born, resting pulse rate (RPR), etc.ConclusionThe ML models using the LightGBM algorithm are efficient to predict insulin sensitivity in the community and primary care settings accurately and might potentially become an efficient and practical tool for insulin sensitivity assessment in these settings.</p

    Molecular simulation study of the influence of different surfactants on the wetting characteristics of anthracite

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    The reduction of dust pollution in coal mines is of great importance both for protection of the environment and for the occupational safety and health of coal mine workers. The reduction of dust from anthracite has been a challenge due to its inherent hydrophobicity and high metamorphism. As a result, surfactants are commonly added to water to improve the wettability of coal, thereby improving the dust reduction efficiency of a water spray system. To clarify from a microscopic perspective the effect of different surfactants on the wettability of anthracite, models for the anthracite-surfactant-water system were established, and adsorption configuration, relative concentration distribution, and the diffusion coefficients of water molecules in the systems were thoroughly investigated with molecular simulations. The results showed the directional arrangement of surfactants in the simulation systems after 150 ps of equilibration, resulting in the reduced surface tension of the water-surfactant solution and enhanced wettability of anthracite. Along the (001) normal direction, the relative concentration of sodium dodecylbenzenesulfonate (SDBS) (15.32), the anthracite-water overlapping area, the diffusion rate of water molecules, and the activity (DSDBS = 0.97 × 10-8 m2·s−1) were maximized, indicating the excellent wettability effect of SDBS. The results of the study are of practical significance for improving the wetting effect of anthracite, improving the dust reduction efficiency, and safeguarding the occupational safety and health of personnel
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