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101.
Amirhossein Moghanian Saba Nasiripour Atiyyeh Koohfar Mohammad Sajjadnejad SeyedMohammad Hosseini Mohsen Taherkhani Zahra Miri Seyed Hesamedin Hosseini Mehrnaz Aminitabar Ali Rashvand 《International Journal of Applied Ceramic Technology》2021,18(5):1430-1441
Bioactive glasses (BGs) have been used for bone formation and bone repair processes in recent years. This study investigated the titanium substitution effect on 58S BGs (Ti-BGs) 60SiO2-(36 − X)CaO-4P2O5-XTiO2 (X = 0, 3, and 5 mol.%) prepared by the sol-gel technique, and the main goal was to find the optimum amount of titanium in Ti-BGs. Synthesized BGs, which were investigated after immersion in simulated body fluid (SBF), were tested by X-ray diffraction (XRD) analysis, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy. Moreover alkaline phosphate (ALP) activity, 3-(4,5dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, and antibacterial studies were employed to investigate the biological properties of Ti-BGs. According to the FTIR and XRD test results, hydroxyapatite (HA) formation on Ti-BGs surfaces was confirmed. Meanwhile, the presence of 5 mol.% compared to 3 mol.% increased the HA grain distribution and their size on the Ti-BGs surface. Additionally, MTT and ALP results confirmed that the optimal amount of titanium substitution in BG was 5 mol.%. Since 5 mol.% Ti incorporated BG (BG-5) had the highest biocompatibility level, antibacterial properties, maximum cell proliferation, and ALP activity among the synthesized Ti-BGs, it is presented as the best candidate for further in vivo investigations. 相似文献
102.
《Ceramics International》2022,48(24):36460-36468
Evaluation of the nonlinear relationship between the surface defect size and fracture strength of ceramics is important for engineering applications. In this study, we aim to predict the apparent nonlinear relationship between the defect size and fracture strength of single-edge notched beams (SENBs) using the finite element method. Specifically, we applied the methodology for predicting fracture strength from microstructure distribution data (relative density, pore size, aspect ratio, and grain size) to a finite element analysis (FEA) model in which the shape and size of the initial defects are defined at notch locations. By reproducing the apparent nonlinearity caused by the competition between the surface and internal defects within the framework of linear elastic fracture mechanics, the effectiveness of the FEA methodology for the evaluation of strength scatter and allowable crack size in ceramics was demonstrated. 相似文献
103.
《Ceramics International》2022,48(2):1814-1819
Sr3Al2-xBxO5Cl2:Eu2+, Dy3+ (x = 0, 0.2, 0.4) long persistent phosphors were prepared via solid-state process. The pristine Sr3Al2O5Cl2:Eu2+, Dy3+ phosphor exhibits orange/red broad band emission around 609 nm, which can be attributed to the electric radiation transitions 4f65 d1→4f7 of Eu2+. Upon the same excitation, the B3+-doped Sr3Al2-xBxO5Cl2:Eu2+, Dy3+ phosphors display red-shift from 609 nm to 625 nm with increasing B3+ concentrations. The XRD patterns show that Al3+ can be replaced by B3+ in the host lattice at the tetrahedral site, which causes lattice contraction and crystal field enhancement, and thereafter achieves the red-shift on the emission spectrum. The XPS investigation provides direct evidence of the dominant 2-valent europium in the phosphor, which can be ascribed for the broad band emission of the prepared phosphors. The afterglow of all phosphors show standard double exponential decay behavior, and the afterglow of Sr3Al2O5Cl2:Eu2+, Dy3+is rather weak, while the sample co-doped with B3+shows longer and stronger afterglow, as confirmed after the curve simulation. The analysis of thermally stimulated luminescence showed that, when B3+ is introduced, a much deeper trap is created, and the density of the electron trap is also significantly increased. As a result, B3+ ions caused redshift and enhanced afterglow for the Sr3Al2-xBxO5Cl2:Eu2+, Dy3+ phosphor. 相似文献
104.
Junyu Chen Yuze Li Yuming Jiang Liucheng Mao Mi Lai Lixia Jiang Huihui Liu Zongxiu Nie 《Advanced functional materials》2021,31(52):2106743
Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO2/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO2/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine. 相似文献
105.
Qiang Liu Xinyu Mao Xiaoying Li Penghui Chen Xin Liu Ziyu Liu Danyang Zhu Haohong Chen Tengfei Xie Jiang Li 《Journal of the American Ceramic Society》2021,104(10):4927-4931
0.5 at.% Cr:ZnGa2O4 precursor was synthesized by the co-precipitation method with nitrates as raw materials, using ammonium carbonate as the precipitant. Low-agglomerated Cr:ZnGa2O4 powders with an average particle size of 43 nm were obtained by calcining the precursor at 900℃ for 4 h. Using the powders as starting materials, 0.5 at.% Cr:ZnGa2O4 ceramics with an average grain size of about 515 nm were prepared by presintering at 1150℃ for 5 h in air and HIP post-treatment at 1100℃ for 3 h under 200 MPa Ar. The in-line transmittance of 0.5 at.% Cr:ZnGa2O4 ceramics with a thickness of 1.3 mm reaches 59.5% at the wavelength of 700 nm. The Cr:ZnGa2O4 ceramics can be effectively excited by visible light and produce persistent luminescence at 700 nm. For Cr:ZnGa2O4 transparent ceramics, the brightness of afterglow was larger than 0.32 mcd/m2 after 30 min, which is far superior to that of Cr:ZnGa2O4 persistent luminescence powders. 相似文献
106.
为了研究径向不耦合条件下爆破效果的影响因素,利用AUTODYN-2D对比不耦合系数、不耦合介质、炸药种类对爆破效果的影响规律。结果表明,与耦合装药相比,径向不耦合装药条件下炮孔压力明显降低。对比水介质和空气介质下的爆破效果可知,水介质不耦合条件下,炸药爆炸能量的传递效率更高。炮孔压力与炸药种类密切相关,TNT产生的炮孔压力最大,但作用时间较短,而ANFO和乳化炸药的作用时间较长。 相似文献
107.
108.
Dr. Maria L. Di Paolo Dr. Michael S. Christodoulou Dr. Alessandra M. Calogero Dr. Luca Pinzi Prof. Giulio Rastelli Prof. Daniele Passarella Prof. Graziella Cappelletti Prof. Lisa Dalla Via 《ChemMedChem》2019,14(18):1641-1652
A series of 2-phenyloxazoles bearing an amide group at position 4 were designed and synthesized for evaluation as potential inhibitors of human recombinant monoamine oxidases (hrMAOs). Results of kinetics experiments demonstrated that all compounds behave as competitive MAO inhibitors, with good selectivity toward the MAO-B isoform. The most potent and selective derivatives are characterized by inhibition constant (Ki) values in the sub-micromolar range and a good selectivity index (Ki MAO-A/Ki MAO-B>50). Some derivatives were also found to be able to inhibit MAO activity in nerve growth factor (NGF)-differentiated PC12 cells, taken as a model of neuronal cells. In particular, 2-(2-hydroxyphenyl)-N-phenyloxazole-4-carboxamide (compound 4 a ) may be a promising new scaffold, exerting the highest selectivity and inhibitory effect toward MAOs in NGF-differentiated PC12 cell lysates, without compromising cell viability. Molecular docking analysis allowed a rationalization of the experimentally observed binding affinity and selectivity. 相似文献
109.
Daniela Frasca Maria Romero Alain Diaz Denisse Garcia Seth Thaller Bonnie B. Blomberg 《International journal of molecular sciences》2021,22(4)
Senescent cells accumulate in the adipose tissue (AT) of individuals with obesity and secrete multiple factors that constitute the senescence-associated secretory phenotype (SASP). This paper aimed at the identification of B cells with a SASP phenotype in the AT, as compared to the peripheral blood, of individuals with obesity. Our results show increased expression of SASP markers in AT versus blood B cells, a phenotype associated with a hyper-metabolic profile necessary to support the increased immune activation of AT-derived B cells as compared to blood-derived B cells. This hyper-metabolic profile is needed for the secretion of the pro-inflammatory mediators (cytokines, chemokines, micro-RNAs) that fuel local and systemic inflammation. 相似文献
110.
Process analytics is one of the popular research domains that advanced in the recent years. Process analytics encompasses identification, monitoring, and improvement of the processes through knowledge extraction from historical data. The evolution of Artificial Intelligence (AI)-enabled Electronic Health Records (EHRs) revolutionized the medical practice. Type 2 Diabetes Mellitus (T2DM) is a syndrome characterized by the lack of insulin secretion. If not diagnosed and managed at early stages, it may produce severe outcomes and at times, death too. Chronic Kidney Disease (CKD) and Coronary Heart Disease (CHD) are the most common, long-term and life-threatening diseases caused by T2DM. Therefore, it becomes inevitable to predict the risks of CKD and CHD in T2DM patients. The current research article presents automated Deep Learning (DL)-based Deep Neural Network (DNN) with Adagrad Optimization Algorithm i.e., DNN-AGOA model to predict CKD and CHD risks in T2DM patients. The paper proposes a risk prediction model for T2DM patients who may develop CKD or CHD. This model helps in alarming both T2DM patients and clinicians in advance. At first, the proposed DNN-AGOA model performs data preprocessing to improve the quality of data and make it compatible for further processing. Besides, a Deep Neural Network (DNN) is employed for feature extraction, after which sigmoid function is used for classification. Further, Adagrad optimizer is applied to improve the performance of DNN model. For experimental validation, benchmark medical datasets were used and the results were validated under several dimensions. The proposed model achieved a maximum precision of 93.99%, recall of 94.63%, specificity of 73.34%, accuracy of 92.58%, and F-score of 94.22%. The results attained through experimentation established that the proposed DNN-AGOA model has good prediction capability over other methods. 相似文献