A Comparison of Biomechanical Properties of Implant-Retained Overdenture Based on Precision Attachment Type.

This paper aims to compare, in vitro, the biomechanical properties of an overdenture retained by two bar-retained implants and an overdenture retained by two bar-retained implants with ball attachments. An edentulous mandible model was prepared for the study based on the FRASACO mold with two implants. In the first system, the "rider" type (PRECI-HORIX, CEKA) retention structure and the complete mandibular denture with the matrix were made. In the second system, the "rider" type retention suprastructure was also used. In the distal part, (CEKA) clips were placed symmetrically, and a complete mandibular denture, together with the matrix on the bar, and the clip patrices were made. A numerical model was developed for each system where all elements were positioned and related to geometric relations, as in reality. The FEA analysis (finite element analysis) was carried out for seven types of loads: with vertical forces of 20, 50, and 100 N and oblique forces of 20 and 50 N acting on individual teeth of the denture, namely central incisor, canine, and first molar. Displacements, stresses, and deformations within the systems were investigated. Maximum denture displacement in the first system was 0.7 mm. Maximum bar stress amounted to 27.528 MPa, and implant stress to 23.16 MPa. Maximum denture displacement in the second system was 0.6 mm. Maximum bar stress amounted to 578.6 MPa, that of clips was 136.99 MPa, and that of implants was 51.418 MPa. Clips cause smaller displacement of the overdenture when it is loaded but generate higher stress within the precision elements and implants compared to a denture retained only by a bar. Regardless of the shape of the precision element, small deformations occur that mainly affect the mucosa and the matrix.

Evaluation of human osteoblast metabolic activity in modified titanium-conditioned medium.

To evaluate human osteoblast metabolic activity cultured in medium conditioned with commercially pure titanium after surface treatments with alumina or ceramic grit-blasting followed by acid etching. Commercially available, pure Grade 4 titanium disks were used and subjected to seven different surface modifications: (1) machined (MA)-used as the control group; (2) blasted with Al2O3 (Al2O3); (3) blasted with sintered ceramic (HAS); (4) blasted with non-sintered ceramics (HA); (5) blasted with Al2O3 and etched with HCl/H2SO4 (Al2O3 DE); (6) blasted with sintered ceramic and etched with HCl/H2SO4 (HAS DE), and (7) blasted with non-sintered ceramic and etched with HCl/H2SO4 (HA DE). A samples roughness evaluation test was carried out with an interference microscope, and energy-dispersive X-ray spectroscopy was performed to evaluate the presence of aluminum, phosphorus, and calcium deposited during the titanium surface treatment along with carbon contaminants acquired by the surface during processing. A culture medium conditioned with the respective samples was prepared in five dilutions, and its effect on human osteoblast cell viability was evaluated using the relative viability of cells. Human osteoblast metabolic activity was found to be the most intensive for the Al2O3 DE sample. The lowest activity was observed for the HAS DE. The material's cytocompatibility depended on both the surface roughness and its chemical composition. Etching had a dual effect on cell activity, depending on the chemical composition of the titanium surface after blasting.

Neural Classification of Compost Maturity by Means of the Self-Organising Feature Map Artificial Neural Network and Learning Vector Quantization Algorithm.

Self-Organising Feature Map (SOFM) neural models and the Learning Vector Quantization (LVQ) algorithm were used to produce a classifier identifying the quality classes of compost, according to the degree of its maturation within a period of time recorded in digital images. Digital images of compost at different stages of maturation were taken in a laboratory. They were used to generate an SOFM neural topological map with centres of concentration of the classified cases. The radial neurons on the map were adequately labelled to represent five suggested quality classes describing the degree of maturation of the composted organic matter. This enabled the creation of a neural separator classifying the degree of compost maturation based on easily accessible graphic information encoded in the digital images. The research resulted in the development of original software for quick and easy assessment of compost maturity. The generated SOFM neural model was the kernel of the constructed IT system.