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Objective: Silicon is an effective element in bone biomineralization; hence Si-substituted hydroxyapatite can be a relevant bioceramic as bone materials substitution. Materials and Methods: Stoichiometric hydroxyapatite (HA) and Si-substituted hydroxyapatite (Si-HA) with different contents of Si substitution were synthesized successfully by a hydrothermal method using Ca(NO3)2, (NH4)3PO4 or (NH4)2HPO4 and Si(OCH2CH3)4 (TEOS) as starting materials. Results: Crystalline Phases, chemical composition, microstructure and morphology of synthesized powders were investigated using X-ray diffraction (XRD), Fourier transform IR spectroscopy (FTIR), inductively coupled plasma AES (ICP-AES) and scanning electron microscopy (SEM) techniques. The results proved silicon substitution in hydroxyapatite structure and revealed that the substitution of phosphate groups by silicate groups caused some OH- loss to maintain charge balance and the lattice parameters slightly changed with respect to stoichiometric HA. Conclusion: Si-incorporation reduces the crystallites size of Si-HA and crystallinity, thus the solubility of Si-HA powders increases, and as a result Si- substitution has improved bioactivity behavior of HA. Based on in-vitro tests; soaking and incubating the specimens in simulated body fluid (SBF) and MTT assays (Dimethylthiazol assay), Si-substituted hydroxyapatite is more bioactive than pure hydroxyapatite.

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Objective: One of the major issues in bone tissue engineering is the design and fabrication of bioactive, bioresorbable porous 3D scaffolds capable of maintaining their structure and integrity over a predictable period of time. One such approach is the fabrication of composite scaffolds. Methods: In this study we present fabrication and characterization of novel silk/bioglass-composite scaffolds. Regenerated fibroin was constructed from mulberry silk cocoons and calcium silicophosphate bioactive glass was made by sol-gel processing. For fabrication of a homogenous composite, grained bioglass particles were modified with 3-aminopropyltriethoxysilane coating. Fibroin/bioglass composite scaffolds were fabricated by the freeze-dry technique at different concentrations. Results: Silk protein extract was evaluated by FTIR and XRD methods. FTIR spectrum showed sharp amide peaks at 1655 cm^-1 and 1530 cm^-1 wave lengths, which confirmed the existence of fibroin. XPS analysis demonstrated that the amino groups were established on the surface of the glass powder. The fabricated 3D scaffolds were morphologically analyzed by scanning electron microscopy, which showed uniformly dispersed bioglass particles in all structures. Scaffolds were seeded with human mesenchymal stem cells for 21 days. Conclusion: Considering the cytocompatibility of the scaffolds and osteogenic differentiation during three weeks, it could be concluded that the appropriate combination of structural and biological properties make the silk/bioglass composite scaffold a probable choice for potential use in bone tissue engineering.

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Objective: Biodegradable polycaprolactone/starch composites can be used for bone tissue engineering applications. The effect of the ratio of components on composite properties is of tremendous importance. Methods: Polycaprolactone/starch composite of 80/20 and 70/30 ratios were fabricated by dissolving them in chloroform followed by evaporation of the solvent. Results: The composites were characterized by fourier transform infrared spectroscopy. Their bioactivity was evaluated by studying the apatite formation ability after immersing the specimens in simulated body fluid. The results of compressive test on samples showed that the composite’s modulus and strength approximated that of human trabecular bone. Mass loss in distilled water and starch degradation rate in PBS was evaluated, which showed that the starch ratio was effective in composite degradation. MTT analysis and alkaline phosphatase levels showed that this composite had no toxicity and could increase G-299 cell line osteoblastic activities. Conclusion: The increase in cellular osteoblastic activities and the ability for apatite formation on the composite surface, in addition to the polycaprolactone/starch samples' mechanical properties shows their capability to be used as substitutes for bone. Because this composite degradation rate is controlled by changing the starch ratio, it has the potential for use in bone tissue engineering applications. Samples that have a 70/30 ratio are considered optimal due to their enhanced cellular response and better mechanical properties.

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One of the critical environmental factors that affect the deformation of flexible pavements is the depth temperature of asphalt layers. This is due to the viscoelastic behavior of the asphalt mixtures. The stiffness of the asphalt layers has a significant effect on the structural capacity of flexible pavements. This property is a function of the asphalt layer temperature and changes daily and seasonally. As the temperature increases, the stiffness of the asphalt layer decreases, which increases the stress in the base and subbase layers of the pavement. Therefore, the pavement response to the applied loads is affected by the depth temperature. Hence, the depth temperature of asphalt layers is one of the most important and main factors in the analysis, design, and rehabilitation process of flexible pavements. Some predictive models have been developed to determine the depth temperature of asphalt layers in pavement maintenance and rehabilitation activities. These models, as an alternative to field and laboratory measurements of this factor, are low-cost, rapid, and simple methods to determine the depth temperature of asphalt layers. It should be noted that these models are based on the limited field and laboratory data, therefore, there is a need for developing new models for prediction of the depth temperature of asphalt layers in different traffic and climatic conditions. The objective of this study is to develop a model for predicting the depth temperature of asphalt layers based on climatic data. In recent years, Artificial Neural Networks (ANNs) have shown good performance as a useful tool for modeling physical events. The modeling method used in this study is a Back-Propagation Neural Network (BPNN) model that predicts the average hourly depth temperature of asphalt layers based on several variables, including the time of the day, desired depth from the pavement surface, average hourly air temperature, average speed and direction of the wind, minimum air humidity and total solar radiation. Data was extracted from the Long-Term Pavement Performance (LTPP) database. After extracting and preparing raw data, all the needed data were acquired from different data tables and linked to each other in a database. As a case study, data points collected from pavements in Ohio, USA, has been used for modeling. Also, to ascertain the presence or absence of multicollinearity between independent variables, the Pearson correlation test has been conducted. For this reason, the maximum speed and direction of the wind and maximum air humidity parameters were removed from the data set. According to the results of the Pearson correlation test, the average hourly air temperature has the most powerful impact on the average hourly temperature of the asphalt layer depth (correlation=95.2%). After training and testing the neural network, the performance of the developed model has been evaluated, and results were compared with a non-linear quadratic regression model. The results show that the developed model is more accurate than the regression-based model. In addition, the ability of the developed model in predicting the depth temperature of asphalt layers based on existing climatic data with a very good prediction accuracy (R²=0.96) and very low bias and error has been shown. Furthermore, the performance of the developed model has some restrictions for the prediction of depth temperature of asphalt layers. Other factors such as material characteristics can be scrutinized and applied to enhance the performance and applicability of the model.

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 Introduction: Prenatal exposure to lipopolysaccharide (LPS) can lead to structural damage and CNS dysfunction. The present study aimed to investigate the protective effects of prenatal administration of pycnogenol (PYC) against the negative effects of bacterial LPS on anxiety-like behavior, gonadotropin and sex hormone serum levels, and sperm quality and quantity in the adult male offspring of NMRI mice.
Methods: Pregnant mice were randomly divided into four groups (n = 10 per group): 1. Saline group: received a single dose of saline as solvent of pycnogenol by gavage for 3 days on gestation days 16-18. 2. LPS group: received a single dose of LPS (20 µg/kg, subcutaneously) on gestation day 20. 3. PYC: received 200 mg/kg/day of pycnogenol by gavage for 3 days, intraperitoneally, on gestation days 16-18. 4. LPS + PYC: received a single dose of LPS (20 μg/kg) on gestation day 20 and pycnogenol (200 mg/kg/day) by gavage for 3 days on gestation days 16-18. After maturity/puberty in male pups (60 days old), the anxiety-like behavior test was performed. After the behavioral test, serum levels of gonadotropins (luteinizing hormone, LH, follicle stimulating hormone, FSH), testosterone hormone and sperm quality were assessed.
Results: LPS administration increased anxiety-like behaviors and decreased serum LH and testosterone levels; however, PYC treatment reversed the negative effects of LPS to normal levels.
Conclusion: PYC treatment improves anxiety-like behavior and gonadotropin and testosterone secretions. Therefore, this substance can be used as a protectant and an aphrodisiac agent.