Alginate-Chitosan Membranes for the Encapsulation of Lavender Essential Oil and Development of Biomedical Applications Related to Wound Healing

Biopolymers such as chitosan (CHT) or alginate (ALG) are among the most prominent for health-related applications due to their broad bioactivity. Their combination for the preparation of membranes is hereby proposed as an application for wound healing with the incorporation of lavender essential oil (LEO), widely known for its antioxidant and antimicrobial properties. The preparation of CHT, CHT + LEO, ALG, ALG + LEO, and CHT/ALG + LEO membranes was accomplished, and its composition was analyzed using Fourier Transform Infrared Spectroscopy (FTIR). The water absorption capacity and oil release profile of the membranes revealed higher water uptake capacity when a lower LEO release was obtained. The combined CHT/ALG + LEO film showed a water uptake percentage of 638% after 48 h and a maximum LEO release concentration of 42 mg/L. Cytotoxicity and biocompatibility of the prepared membranes were studied using a HaCaT cell line, with an assessment of cell viability regarding film leachables, DNA quantification, and DAPI-phalloidin staining. The results revealed that the indirect contact of the prepared membranes via its leachables does not compromise cell viability, and upon direct contact, cells do not adhere or proliferate on the surface of the membranes. Moreover, the CHT/ALG + LEO membrane increases cell proliferation, making it suitable for applications in wound healing.

In vitro and in vivo degradation assessment and preventive measures of biodegradable Mg alloys for biomedical applications

Magnesium (Mg) and its alloys have been widely explored as a potential biodegradable implant material. However, the fast degradation of Mg-based alloys under physiological environment has hindered their widespread use for implant applications till date. The present review focuses on in vitro and in vivo degradation of biodegradable Mg alloys, and preventive measures for biomedical applications. Initially, the corrosion assessment approaches to predict the degradation behavior of Mg alloys are discussed along with the measures to control rapid corrosion. Furthermore, this review attempts to explore the correlation between in vitro and in vivo corrosion behavior of different Mg alloys. It was found that the corrosion depends on experimental conditions, materials and the results of different assessment procedures hardly matches with each other. It has been demonstrated the corrosion rate of magnesium can be tailored by alloying elements, surface treatments and heat treatments. Various researches also studied different biocompatible coatings such as dicalcium phosphate dihydrate (DCPD), β-tricalcium phosphate (β-TCP), hydroxyapatite (HA), polycaprolactone (PCL), polylactic acid (PLA), and so on, on Mg alloys to suppress rapid degradation and examine their influence on new bone regeneration as well. This review shows the need for a standard method of corrosion assessment to predict the in vivo corrosion rate based on in vitro data, and thus reducing the in vivo experimentation.

Segmentation Method of Time-Lapse Microscopy Images with the Focus on Biocompatibility Assessment

Biocompatibility testing of new materials is often performed in vitro by measuring the growth rate of mammalian cancer cells in time-lapse images acquired by phase contrast microscopes. The growth rate is measured by tracking cell coverage, which requires an accurate automatic segmentation method. However, cancer cells have irregular shapes that change over time, the mottled background pattern is partially visible through the cells and the images contain artifacts such as halos. We developed a novel algorithm for cell segmentation that copes with the mentioned challenges. It is based on temporal differences of consecutive images and a combination of thresholding, blurring, and morphological operations. We tested the algorithm on images of four cell types acquired by two different microscopes, evaluated the precision of segmentation against manual segmentation performed by a human operator, and finally provided comparison with other freely available methods. We propose a new, fully automated method for measuring the cell growth rate based on fitting a coverage curve with the Verhulst population model. The algorithm is fast and shows accuracy comparable with manual segmentation. Most notably it can correctly separate live from dead cells.