Evaluation of a novel nanocrystalline hydroxyapatite powder and a solid hydroxyapatite/Chitosan-Gelatin bioceramic for scaffold preparation used as a bone substitute material

Artificially fabricated hydroxyapatite (HAP) shows excellent biocompatibility with various kinds of cells and tissues which makes it an ideal candidate for a bone substitute material. In this study, hydroxyapatite nanoparticles have been prepared by using the wet chemical precipitation method using calcium nitrate tetra-hydrate [Ca(NO₃)₂.4H₂O] and di-ammonium hydrogen phosphate [(NH₄)₂ HPO₄] as precursors. The composite scaffolds have been prepared by a freeze-drying method with hydroxyapatite, chitosan, and gelatin which form a 3D network of interconnected pores. Glutaraldehyde solution has been used in the scaffolds to crosslink the amino groups (|NH₂) of gelatin with the aldehyde groups (|CHO) of chitosan. The X-ray diffraction (XRD) performed on different scaffolds indicates that the incorporation of a certain amount of hydroxyapatite has no influence on the chitosan/gelatin network and at the same time, the organic matrix does not affect the crystallinity of hydroxyapatite. Transmission electron microscope (TEM) images show the needle-like crystal structure of hydroxyapatite nanoparticle. Scanning Electron Microscope (SEM) analysis shows an interconnected porous network in the scaffold where HAP nanoparticles are found to be dispersed in the biopolymer matrix. Fourier transforms infrared spectroscopy (FTIR) confirms the presence of hydroxyl group (OH^-) , phosphate group (PO^3-₄) , carbonate group (CO^2-₃) , imine group (C=N), etc. TGA reveals the thermal stability of the scaffolds. The cytotoxicity of the scaffolds is examined qualitatively by VERO (animal cell) cell and quantitatively by MTTassay. The MTT-assay suggests keeping the weight percentage of glutaraldehyde solution lower than 0.2%. The result found from this study demonstrated that a proper bone replacing scaffold can be made up by controlling the amount of hydroxyapatite, gelatin, and chitosan which will be biocompatible, biodegradable, and biofriendly for any living organism.     

Properties of MgFe2O4 Nanoparticles Synthesized by Ultrasonic Aerosol Pyrolysis for Biomedical Applications

Physics of the Solid State - We present the data of studies on the structure, phase states, and magnetic properties of magnetic nanoparticles (MNPs) of magnesium ferrite spinel (MgFe2O4),...     

Insight into 3D micro‐CT data: exploring segmentation algorithms through performance metrics

Three‐dimensional (3D) micro‐tomography (µ‐CT) has proven to be an important imaging modality in industry and scientific domains. Understanding the properties of material structure and behavior has produced many scientific advances. An important component of the 3D µ‐CT pipeline is image partitioning (or image segmentation), a step that is used to separate various phases or components in an image. Image partitioning schemes require specific rules for different scientific fields, but a common strategy consists of devising metrics to quantify performance and accuracy. The present article proposes a set of protocols to systematically analyze and compare the results of unsupervised classification methods used for segmentation of synchrotron‐based data. The proposed dataflow for Materials Segmentation and Metrics (MSM) provides 3D micro‐tomography image segmentation algorithms, such as statistical region merging (SRM), k‐means algorithm and parallel Markov random field (PMRF), while offering different metrics to evaluate segmentation quality, confidence and conformity with standards. Both experimental and synthetic data are assessed, illustrating quantitative results through the MSM dashboard, which can return sample information such as media porosity and permeability. The main contributions of this work are: (i) to deliver tools to improve material design and quality control; (ii) to provide datasets for benchmarking and reproducibility; (iii) to yield good practices in the absence of standards or ground‐truth for ceramic composite analysis.     

Surface extenders and an optimal pore size promote high dynamic binding capacities of antibodies on cation exchange resins

Increased recombinant protein expression yields and a large installed base of manufacturing facilities designed for smaller bulk sizes has led to the need for high capacity chromatographic resins. This work explores the impact of three pore sizes (with dextran distribution coefficients of 0.4, 0.53, and 0.64), dextran surface extender concentration (11–20 mg/mL), and ligand density (77–138 μmol H+/mL resin) of cation exchange resins on the dynamic binding capacity of a therapeutic antibody. An intermediate optimal pore size was identified from three pore sizes examined. Increasing ligand density was shown to increase the critical ionic strength, while increasing dextran content increased dynamic binding capacity mainly at the optimal pore size and lower conductivities. Dynamic binding capacity as high as 200 mg/mL was obtained at the optimum pore size and dextran content.     

Ion exchange chromatography of monoclonal antibodies: Effect of resin ligand density on dynamic binding capacity

Dynamic binding capacity (DBC) of a monoclonal antibody on agarose based strong cation exchange resins is determined as a function of resin ligand density, apparent pore size of the base matrix, and protein charge. The maximum DBC is found to be unaffected by resin ligand density, apparent pore size, or protein charge within the tested range. The critical conductivity (conductivity at maximum DBC) is seen to vary with ligand density. It is hypothesized that the maximum DBC is determined by the effective size of the proteins and the proximity to which they can approach one another. Once a certain minimum resin ligand density is supplied, additional ligand is not beneficial in terms of resin capacity. Additional ligand can provide flexibility in designing ion exchange resins for a particular application as the critical conductivity could be matched to the feedstock conductivity and it may also affect the selectivity.