RELATING CELLULAR ASSOCIATION WITH LIPOSOME CYTOTOXICITY IN HUMAN ENDOTHELIAL CELLS

INTRODUCTION Interactions with the endothelium play a key role in the behaviour of intravenously administered nanoparticle drug carriers[1]. Hence, quantifying cellular association (membrane adhesion and cell internalization) of liposomes with endothelial cells is an effective screening method of biocompatibility and success of new drug carriers. Current methods are inaccurate as concentration does not necessarily equate to local cellular association. The focus of this experiment is to quantify the cellular association between liposomes and two types of human endothelial cells and compare the associations with cells’ cytotoxic response. Cellular association of liposomes as well as cell viability were quantified on cellular level at different concentrations of liposomes. METHODS Two different types of cells, Human Umbilical Vein Endothelial cell, which is a common cell type used in vitro studies, and Human MicroVascular Cell, which is more accurate representation of in vivo, were used[2]. HUVEC and HMVEC were cultured and passaged onto chamber slides using standard cell culture techniques. The confluent cells were exposed to fluorescent liposomes with hydrodynamic diameter of 90.4 nm at concentrations ranging from 0.08nM to 8nM for 24 hours, membrane stained with CellMask Deep Red and fixed with paraformaldehyde, following same protocols for both types of cells. Cell viability on exposure to the same concentration range of liposomes was determined using Vialight assay using manufacturer protocols. Z-stacks of the treated cells were obtained using Olympus Fluoview FV1000 confocal microscope. Region of interest, limited by cell membranes, was set using the membrane stain channel using ImageJ. The region of interest was superimposed onto the fluorescent liposome channel to determine exclusively the fluorescence of cell adhered and cell internalized liposomes RESULTS Compared to HUVECs, higher cellular association of liposomes was observed for HMVC as shown in Figure 1.While cellular association of liposomes increased with concentration, cell viability was in the range of 85 to nearly 100% for the concentration range of 0.08-4 nM with no significant difference. Only at 8 nM, cell viability decreased significantly to approximately 62 %. DISCUSSION AND CONCLUSIONS Liposome cellular association provide insight into the cytotoxicity and the endothelial cytotoxicity of the liposomes at low concentration of 8nM raises cautions on documented innocuous properties of liposomes. Cytotoxicity and cellular association upon comparison showed exponential relationship. Because the cytotoxicity and cellular association relationship is exponential, slight over-administration can cause severe toxicity. 8nM is lower than concentration of current intravenous liposome-based drug doxorubicin[3]. High toxicity and exponential relationship raise caution on the importance of proper safe dosage

RELATING QUANTUM DOT ASSOCIATION WITH HUMAN ENDOTHELIAL CELLS WITH THEIR CYTOTOXIC EFFECTS

INTRODUCTION Advances in the field of nanotechnology have enabled researchers to pursue biomedical applications of nanoparticles. Quantum dots are commonly used fluorescent probes because they are brighter and less prone to photobleaching than other fluorophores [1]. However, despite the advantages, potential for toxicity must be acknowledged. Quantum dots are commonly made with toxic metal elements, which can cause oxidative stress [2]. Cadmium ions have been shown to disrupt mitochondria activity, leading to cell death [2]. Quantum dots have been shown to attach to the cell membrane as well as be internalized through endocytic mechanisms [3]. In this study, we aim to quantify quantum dot association and compare results from cytotoxicity assays for identical conditions, relating cellular association with cytotoxicity. METHODS Human Umbilical Vein Endothelial Cells (HUVECs) and Human Micro-vascular Endothelial Cells (HMVECs) were cultured in static conditions in 8-well chamber slides then exposed to amino-PEG quantum dots at a concentration of 0.2nM to 200nM. After exposure for 24 hours, the cells were washed, fixed, and stained. Z-stacks were obtained using an Olympus Fluoview FV1000 confocal microscope. Images were analyzed using ImageJ software to quantify mean fluorescence intensity within the defined region of interest, selected from the boundaries of stained cell membranes. Statistical analysis using one-way Analysis of Variance (ANOVA) and post-hoc Tukey HSD test was performed. Finally, Vialight assay was used to test cell viability after exposure to quantum dots under the same experimental conditions used for association experiments. RESULTS Exposure to different concentrations of quantum dots results in significant changes in the observed fluorescence intensity per area. Non-linear dependence of cellular association of quantum dots on exposure concentration was observed. A representative example of mean fluorescence intensity of quantum dots associated with HUVECs is shown in Figure 1.A significant decrease in the viability of HUVECs was observed on exposure to quantum dots (30-50% cell viability relative to 100% for non-exposed cells). However, no significant difference in cell viability was observed between 0.2nM to 200nM concentrations. DISCUSSION AND CONCLUSIONS Nanoparticle association studies play a vital role in predicting cell viability in nanoparticle cytotoxicity studies. The non-linear trend observed suggests that for the range of concentrations examined, cellular association does not increase linearly with exposure concentration, and that cytotoxicity can be related to association, rather than just to exposure concentration. This experiment provides an approach to advance future studies relating cellular association to cytotoxicity

Essential properties and explanation effectiveness of explainable artificial intelligence in healthcare: A systematic review

Background: Significant advancements in the field of information technology have influenced the creation of trustworthy explainable artificial intelligence (XAI) in healthcare. Despite improved performance of XAI, XAI techniques have not yet been integrated into real-time patient care. Objective: The aim of this systematic review is to understand the trends and gaps in research on XAI through an assessment of the essential properties of XAI and an evaluation of explanation effectiveness in the healthcare field. Methods: A search of PubMed and Embase databases for relevant peer-reviewed articles on development of an XAI model using clinical data and evaluating explanation effectiveness published between January 1, 2011, and April 30, 2022, was conducted. All retrieved papers were screened independently by the two authors. Relevant papers were also reviewed for identification of the essential properties of XAI (e.g., stakeholders and objectives of XAI, quality of personalized explanations) and the measures of explanation effectiveness (e.g., mental model, user satisfaction, trust assessment, task performance, and correctability). Results: Six out of 882 articles met the criteria for eligibility. Artificial Intelligence (AI) users were the most frequently described stakeholders. XAI served various purposes, including evaluation, justification, improvement, and learning from AI. Evaluation of the quality of personalized explanations was based on fidelity, explanatory power, interpretability, and plausibility. User satisfaction was the most frequently used measure of explanation effectiveness, followed by trust assessment, correctability, and task performance. The methods of assessing these measures also varied. Conclusion: XAI research should address the lack of a comprehensive and agreed-upon framework for explaining XAI and standardized approaches for evaluating the effectiveness of the explanation that XAI provides to diverse AI stakeholders