Correction: A continuum membrane model can predict curvature sensing by helix insertion

Correction for ‘A continuum membrane model can predict curvature sensing by helix insertion’ by Yiben Fu et al., Soft Matter, 2021, 17, 10649–10663, DOI: 10.1039/D1SM01333E.

Assessment of the Wound Healing Property of the Ethanolic Seed Extract of Eleusine coracana Linn using the Chorioallantoic Membrane Model

Access to readily available material for wound healing is very important. The wound healing property of Eleusine coracana a food source in Nigeria was therefore investigated. The ethanolic crude extract of the seed flour was prepared using maceration and qualitative phytochemical screening was carried out on the crude extract using standard methods. The antimicrobial activity of the E. coracana extract was determined using the disc diffusion method against E. coli, S. aureus, P. aeruginosa, and C. tetani. The wound healing property assay was carried out using the Chorioallantoic Membrane Model (CAM) at 50mg, 100mg, 150mg, and 200mg/ml concentration with the basic Fibroblast Growth Factor (bFGF) as the positive control. The crude extract was further fractionated into Hexane, Methanolic, and Aqueous fractions and then subjected to amino acid content analysis using the Applied Biosystems Phenylthiohydantoin (PTH) Amino Acid Analyzer. The phytochemical screening reveals the presence of alkaloids, steroids, terpenes, flavonoids, carbohydrates, glycoside, and protein. E. coli and S. aureus were susceptible to the E. coracana extract at a Minimum Inhibitory Concentration (MIC) of 50µg/ml while the P. aeruginosa was only susceptible at 200µg/ml and C. tetani was not susceptible at all the concentrations used. An increase in percentage angiogenesis was observed at all doses of the extract used indicating good wound healing properties. The amino acid profile reveals the presence of glycine, a proline that is important in wound healing. The E. coracana seeds, therefore, have wound healing properties based on the CAM model.

Sinapic Acid Release at the Cell Level by Incorporation into Nanoparticles: Experimental Evidence Using Biomembrane Models

Sinapic acid (SA), belonging to the phenylpropanoid family, and its derivatives are secondary metabolites found in the plant kingdom. In recent years, they have drawn attention because of their various biological activities, including neuroprotective effects. In this study, SA was incorporated into two different nanoparticle systems, solid lipid nanoparticles (SLN) and nanostructured lipid carriers (NLC). The influence of different concentrations of SA on the nanoparticle systems was evaluated. It was studied the efficacy of the nanoparticle systems to release the active ingredient at cell level through the use of models of biological membranes represented by multilamellar vesicles (MLV) of dimyristoylphosphatidylcholine (DMPC) and conducting kinetic studies by placing in contact SLN and NLC, both unloaded and loaded with two different amounts of SA, with the same biological membrane model. Differential scanning calorimetry (DSC) was used for these studies. The results indicated a different distribution of SA within the two nanoparticle systems and that NLC are able to incorporate and release SA inside the structure of the biological membrane model.

A data-driven approach to modeling cancer cell mechanics during microcirculatory transport

In order to understand the effect of cellular level features on the transport of circulating cancer cells in the microcirculation, there has been an increasing reliance on high-resolution in silico models. Accurate simulation of cancer cells flowing with blood cells requires resolving cellular-scale interactions in 3D, which is a significant computational undertaking warranting a cancer cell model that is both computationally efficient yet sufficiently complex to capture relevant behavior. Given that the characteristics of metastatic spread are known to depend on cancer type, it is crucial to account for mechanistic behavior representative of a specific cancer’s cells. To address this gap, in the present work we develop and validate a means by which an efficient and popular membrane model-based approach can be used to simulate deformable cancer cells and reproduce experimental data from specific cell lines. Here, cells are modeled using the immersed boundary method (IBM) within a lattice Boltzmann method (LBM) fluid solver, and the finite element method (FEM) is used to model cell membrane resistance to deformation. Through detailed comparisons with experiments, we (i) validate this model to represent cancer cells undergoing large deformation, (ii) outline a systematic approach to parameterize different cell lines to optimally fit experimental data over a range of deformations, and (iii) provide new insight into nucleated vs. non-nucleated cell models and their ability to match experiments. While many works have used the membrane-model based method employed here to model generic cancer cells, no quantitative comparisons with experiments exist in the literature for specific cell lines undergoing large deformation. Here, we describe a phenomenological, data-driven approach that can not only yield good agreement for large deformations, but explicitly detail how it can be used to represent different cancer cell lines. This model is readily incorporated into cell-resolved hemodynamic transport simulations, and thus offers significant potential to complement experiments towards providing new insights into various aspects of cancer progression.

A Study of the Interaction of a New Benzimidazole Schiff Base with Synthetic and Simulated Membrane Models of Bacterial and Mammalian Membranes

Biological membranes are complex dynamic systems composed of a great variety of carbohydrates, lipids, and proteins, which together play a pivotal role in the protection of organisms and through which the interchange of different substances is regulated in the cell. Given the complexity of membranes, models mimicking them provide a convenient way to study and better understand their mechanisms of action and their interactions with biologically active compounds. Thus, in the present study, a new Schiff base (Bz-Im) derivative from 2-(m-aminophenyl)benzimidazole and 2,4-dihydroxybenzaldehyde was synthesized and characterized by spectroscopic and spectrometric techniques. Interaction studies of (Bz-Im) with two synthetic membrane models prepared with 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC) and DMPC/1,2-dimyristoyl-sn-glycero-3-phosphoglycerol (DMPG) 3:1 mixture, imitating eukaryotic and prokaryotic membranes, respectively, were performed by applying differential scanning calorimetry (DSC). Molecular dynamics simulations were also developed to better understand their interactions. In vitro and in silico assays provided approaches to understand the effect of Bz-Im on these lipid systems. The DSC results showed that, at low compound concentrations, the effects were similar in both membrane models. By increasing the concentration of Bz-Im, the DMPC/DMPG membrane exhibited greater fluidity as a result of the interaction with Bz-Im. On the other hand, molecular dynamics studies carried out on the erythrocyte membrane model using the phospholipids POPE (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine), SM (N-(15Z-tetracosenoyl)-sphing-4-enine-1-phosphocholine), and POPC (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine) revealed that after 30 ns of interaction, both hydrophobic interactions and hydrogen bonds were responsible for the affinity of Bz-Im for PE and SM. The interactions of the imine with POPG (1-Palmitoyl-2-Oleoyl-sn-Glycero-3-Phosphoglycerol) in the E. coli membrane model were mainly based on hydrophobic interactions.