The 3D printing technologies used for medical applications are mostly based on paste extruders. These are designed for high capacity, and thus often feature large material reservoirs and large diameter nozzles. A major challenge for most 3D printing platforms is a compromise between speed, accuracy, and/or volume/mass of moving elements. To address these issues, we integrated a peristaltic pump into a bioprinter. That allowed for combining the most important requirements: high precision, a large material reservoir, and safety of biological material. The system of a fully heated nozzle and a cooled print bed were developed to maintain the optimal hydrogel temperature and crosslinking speed. Our modifications of the bioprinter design improved the mechanical properties of the printouts and their accuracy while maintaining the maximal survival rate of cells and increasing the capacity of the bioink reservoir.
Cemented arthroplasty is a common process to fix prostheses when a patient becomes older and his/her bone quality deteriorates. The applied cements are biocompatible, can transfer loads, and dampen vibrations, but do not provide antibacterial protection. The present work is aimed at the development of cement with antibacterial effectivity achieved with the implementation of nanoparticles of different metals. The powders of Ag, Cu with particles size in a range of 10–30 nm (Cu10) and 70–100 nm (Cu70), AgCu, and Ni were added to PMMA cement. Their influence on compression strength, wettability, and antibacterial properties of cement was assessed. The surface topography of samples was examined with biological and scanning electron microscopy. The mechanical properties were determined by compression tests. A contact angle was observed with a goniometer. The biological tests included an assessment of cytotoxicity (XTT test on human cells Saos-2 line) and bacteria viability exposure (6 months). The cements with Ag and Cu nanopowders were free of bacteria. For AgCu and Ni nanoparticles, the bacterial solution became denser over time and, after 6 months, the bacteria clustered into conglomerates, creating a biofilm. All metal powders in their native form in direct contact reduce the number of eukaryotic cells. Cell viability is the least limited by Ag and Cu particles of smaller size. All samples demonstrated hydrophobic nature in the wettability test. The mechanical strength was not significantly affected by the additions of metal powders. The nanometal particles incorporated in PMMA-based bone cement can introduce long-term resistance against bacteria, not resulting in any serious deterioration of compression strength.
Most of the literature on utility pattern mining (UPM) assumes that the particular patterns' utility in known in advance. Concurrently, in frequent pattern mining (FPM) it is assumed that all patterns take the same value. In reality, the information about the utility of patterns is not or hardly available in most cases. Moreover, the utility and frequency of the particular pattern are not directly proportional. An algorithm for estimating a generic pattern utility has been recently proposed, but the numeric results might be difficult to interpret. In particular, in datasets with many independent instances or groups. In this paper, we present an approach to generating utility bitmaps that provide visual representation of the numeric data obtained using generic pattern utility algorithm. We demonstrate validity of this approach on two datasets: PAMAP2 Physical Activity Monitoring Data Set, an open dataset from the UCI Machine Learning Repository, and an ECG dataset collected using Biopac Student Lab during Ruffier's test. For PAMAP2 dataset, utility bitmaps allow for immediate separation of various physical activities. Variation between participants are present, but do not overshadow differences between the activity types. For the ECG dataset, utility bitmaps immediately indicate age and fitness differences between the participants, even thought this information was not available to the algorithm. In both cases, partial similarity in bitmaps can be traced back to partial similarity in activities or participants generating the data. Based on these tests, the approach seems to be promising for exploratory analysis of large collections of long time series and possibly other sequential patterns such as distance series common in sports data analysis and depth series common in petroleum engineering.
Alginate-gelatin hydrogels are the most commonly used materials for 3D bioprinting.Their printability depends on their properties, and these derive from the way they are prepared and their very composition. Therefore, the aim of the study was to investigate the type of solvent (deionized water, phosphate buffer, and culture medium) and contents of gelatin in the composition of hydrogel (2% wt/vol alginate, 6% and 9% wt/vol of gelatin) on their biological, physicochemical, and mechanical properties, as well as printability and the ability of cells to proliferate in the printed structures. The results obtained revealed that all the manufactured hydrogel materials are biocompatible. The use of deionized water as a solvent results in the highest degree of cross-linking of hydrogels, thus obtaining a polymer with the highest rigidity. Moreover, an increase in gelatin content leads to an increase in the Young's modulus value, irrespectively of the solvent in which the hydrogels were prepared. Based on the chemical structure, it is more reasonable to use a culture medium for bioink preparation due to free NH and NH 2 groups being present, which are ligands for cell attachment and their proliferation. For the selected material (2A9GM), the printability and high viability of the cells after printing were confirmed. In this case, the concentration of the cross-linking agent influences gelatin amount release and calcium ions release, and these two processes determine the change in the viability of the cells encapsulated in the bioink.
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