Osseointegration of oral implants after delayed placement in rabbits: a microcomputed tomography and histomorphometric study

Item does not contain fulltextPurpose: This study compared osseointegration of implants placed 14 days after implant site preparation with that of immediately placed implants in rabbit femurs. Materials and Methods: Implants were placed bilaterally in the femoral condyles of 12 rabbits. On one side, the implants were placed 14 days after osteotomy, and the other side received implants immediately after osteotomy. Healing was assessed by microcomputed tomography and histomorphometry. Results: The delayed implants (placed 14 days after osteotomy) showed better osseointegration than the immediately placed implants. Bone-to-implant contact and bone volume, as assessed by histomorphometry and microcomputed tomography, were significantly higher for the implants placed after 14 days. Conclusions: From this study, it can be concluded that early osteotomy bed preparation and placement of implants after a 2-week delay predisposes to better bone-implant interface healing

Vis‐nir spectroscopy and satellite landsat‐8 oli data to map soil nutrients in arid conditions: A case study of the northwest coast of egypt

The mapping of soil nutrients is a key issue for numerous applications and research fields ranging from global changes to environmental degradation, from sustainable soil management to the precision agriculture concept. The characterization, modeling and mapping of soil properties at diverse spatial and temporal scales are key factors required for different environments. This paper is focused on the use and comparison of soil chemical analyses, Visible near infrared and shortwave infrared VNIR‐SWIR spectroscopy, partial least‐squares regression (PLSR), Ordinary Kriging (OK), and Landsat‐8 operational land imager (OLI) images, to inexpensively analyze and predict the content of different soil nutrients (nitrogen (N), phosphorus (P), and potassium (K)), pH, and soil organic matter (SOM) in arid conditions. To achieve this aim, 100 surface samples of soil were gathered to a depth of 25 cm in the Wadi El‐Garawla area (the northwest coast of Egypt) using chemical analyses and reflectance spectroscopy in the wavelength range from 350 to 2500 nm. PLSR was used firstly to model the relationship between the averaged values from the ASD spectroradiometer and the available N, P, and K, pH and SOM contents in soils in order to map the predicted value using Ordinary Kriging (OK) and secondly to retrieve N, P, K, pH, and SOM values from OLI images. Thirty soil samples were selected to verify the validity of the results. The randomly selected samples included the spatial diversity and characteristics of the study area. The prediction of available of N, P, K pH and SOM in soils using VNIR‐SWIR spectroscopy showed high performance (where R2 was 0.89, 0.72, 0.91, 0.65, and 0.75, respectively) and quite satisfactory results from Landsat‐8 OLI images (correlation R2 values 0.71, 0.68, 0.55, 0.62 and 0.7, respectively). The results showed that about 84% of the soils of Wadi El‐Garawla are characterized by low‐to‐moderate fertility, while about 16% of the area is characterized by high soil fertility. © MDPI AG. All rights reserved

Imaging of cardiopulmonary diseases

Calcium phosphate (CaP) ceramic coatings have been used to enhance the biocompatibility and osteoconductive properties of metallic implants. The chemical composition of these ceramic coatings is an important parameter, which can influence the final bone performance of the implant. In this study, the effect of phase composition of CaP-sputtered coatings was investigated on in vitro dissolution behavior and in vivo bone response. Coatings were prepared by a radio frequency (RF) magnetron sputtering technique; three types of CaP target materials were used to obtain coatings with different stoichiometry and calcium to phosphate ratios (hydroxyapatite (HA), alpha-tricalciumphosphate (alpha-TCP), and tetracalciumphosphate (TTCP)) were compared with non-coated titanium controls. The applied ceramic coatings were characterized by X-ray diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy, and inductively coupled plasma optical emission spectroscopy. The in vitro dissolution/precipitation of the CaP coatings was evaluated using immersion tests in simulated body fluid (SBF). To mimic the in vivo situation, identical CaP coatings were also evaluated in a femoral condyle rabbit model. TCPH and TTCPH showed morphological changes during 4-week immersion in SBF. The results of bone implant contact (BIC) and peri-implant bone volume (BV) showed a similar response for all experimental coatings. An apparent increase in tartrate resistant acid phosphatase (TRAP) positive staining was observed in the peri-implant region with decreasing coating stability. In conclusion, the experimental groups showed different coating properties when tested in vitro and an apparent increase in bone remodeling with increasing coating dissolution in vivo

On the use of multivariate analysis and land evaluation for potential agricultural development of the northwestern coast of Egypt

The development of the agricultural sector is considered the backbone of sustainable development in Egypt. While the developing countries of the world face many challenges regarding food security due to rapid population growth and limited agricultural resources, this study aimed to assess the soils of Sidi Barrani and Salloum using multivariate analysis to determine the land capability and crop suitability for potential alternative crop uses, based on using principal component analysis (PCA), agglomerative hierarchical cluster analysis (AHC) and the Almagra model of MicroLEIS. In total, 24 soil profiles were dug, to represent the geomorphic units of the study area, and the soil physicochemical parameters were analyzed in laboratory. The land capability assessment was classified into five significant classes (C1 to C5) based on AHC and PCA analyses. The class C1 represents the highest capable class while C5 is assigned to lowest class. The results indicated that about 7% of the total area was classified as highly capable land (C1), which is area characterized by high concentrations of macronutrients (N, P, K) and low soil salinity value. However, about 52% of the total area was assigned to moderately high class (C2), and 29% was allocated in moderate class (C3), whilst the remaining area (12%) was classified as the low (C4) and not capable (C5) classes, due to soil limitations such as shallow soil depth, high salinity, and increased erosion susceptibility. Moreover, the results of the Almagra soil suitability model for ten crops were described into four suitability classes, while about 37% of the study area was allocated in the highly suitable class (S2) for wheat, olive, alfalfa, sugar beet and fig. Furthermore, 13% of the area was categorized as highly suitable soil (S2) for citrus and peach. On the other hand, about 50% of the total area was assigned to the marginal class (S4) for most of the selected crops. Hence, the use of multivariate analysis, mapping land capability and modeling the soil suitability for diverse crops help the decision makers with regard to potential agricultural development. © 2020 by the authors

Modeling land suitability for rice crop using remote sensing and soil quality indicators: The case study of the nile delta

Today, the global food security is one of the most pressing issues for humanity, and, according to Food and Agriculture Organisation (FAO), the increasing demand for food is likely to grow by 70% until 2050. In this current condition and future scenario, the agricultural production is a critical factor for global food security and for facing the food security challenge, with specific reference to many African countries, where a large quantities of rice are imported from other continents. According to FAO, to face the Africa’s inability to reach self-sufficiency in rice, it is urgent “to redress to stem the trend of over-reliance on imports and to satisfy the increasing demand for rice in areas where the potential of local production resources is exploited at very low levels” The present study was undertaken to design a new method for land evaluation based on soil quality indicators and remote sensing data, to assess and map soil suitability for rice crop. Results from the investigations, performed in some areas in the northern part of the Nile Delta, were compared with the most common approaches, two parametric (the square root, Storie methods) and two qualitative (ALES and MicrioLEIS) methods. From the qualitative point of view, the results showed that: (i) all the models provided partly similar outputs related to the soil quality assessments, so that the distinction using the crop productivity played an important role, and (ii) outputs from the soil suitability models were consistent with both the satellite Sentinel-2 Normalize Difference Vegetation Indices (NDVI) during the crop growth and the yield production. From the quantitative point of view, the comparison of the results from the diverse approaches well fit each other, and the model, herein proposed, provided the highest performance. As a whole, a significant increasing in R2 values was provided by the model herein proposed, with R2 equal to 0.92, followed by MicroLES, Storie, ALES and Root as R2 with value equal to 0.87, 0.86, 0.84 and 0.84, respectively, with increasing percentage in R2 equal to 5%, 6% and 8%, respectively. Furthermore, the proposed model illustrated that around (i) 44.44% of the total soils of the study area are highly suitable, (ii) 44% are moderately suitable, and (iii) approximately 11.56% are unsuitable for rice due to their adverse physical and chemical soil properties. The approach herein presented can be promptly re-applied in arid region and the quantitative results obtained can be used by decision makers and regional governments. © 2020 by the authors. Licensee MDPI, Basel, Switzerland