Nowadays, biomedicine is a multidisciplinary science that requires a very broad approach to the study and analysis of various phenomena essential for a better understanding of human health. This study deals with the use of numerical simulations to better understand the processes of cancer viability and apoptosis in treatment with commercial chemotherapeutics. Starting from many experiments examining cell viability in real-time, determining the type of cell death and genetic factors that control these processes, a lot of numerical results were obtained. These in vitro test results were used to create a numerical model that gives us a new angle of observation of the proposed problem. Model systems of colon and breast cancer cell lines (HCT-116 and MDA-MB-231), as well as a healthy lung fibroblast cell line (MRC-5), were treated with commercial chemotherapeutics in this study. The results indicate a decrease in viability and the appearance of predominantly late apoptosis in the treatment, a strong correlation between parameters. A mathematical model was created and employed for a better understanding of investigated processes. Such an approach is capable of accurately simulating the behavior of cancer cells and reliably predicting the growth of these cells.

Deterministic and stochastic models of Brownian motion in ferrofluids are of interest to researchers, especially those related to drug delivery systems. The Brownian motion of nanoparticles in a ferrofluid environment was theoretically analyzed in this research. The state of the art in clinical drug delivery systems using ferromagnetic particles is briefly presented. The motion of the nanoparticles in an external field and as a random variable is elaborated by presenting a theoretical model. We analyzed the theoretical model and performed computer simulation by using Maple software. We used simple low-dimensional deterministic systems that can exhibit diffusive behavior. The ferrofluid in the gravitational field without the presence of an external magnetic field in the xy plane was observed. Control parameter p was mapped as related to the fluid viscosity. Computer simulation showed that nanoparticles can exhibit deterministic patterns in a chaotic model for certain values of the control parameter p. Linear motion of the particles was observed for certain values of the parameter p, and for other values of p, the particles move randomly without any rule. Based on our numerical simulation, it can be concluded that the motion of nanoparticles could be controlled by inherent material properties and properties of the surrounding media, meaning that the delivery of drugs could possibly be executed by a ferrofluid without an exogenous power propulsion strategy. However, further studies are still needed.

Electrospinning is highly used technique in the tissue engineering field, particularly in biomedical application [1]. The constricted concepts of this process are based on generate nonwoven nanofibers. The method involves high voltage electricity which is applied to the liquid solution and a collector, which lets the solution force out from a nozzle forming a jet. The jet formed fibers under influence of electrostatic forces concentrated and deposited these on the collector. Main objective of this study was to fabricate gelatin scaffolds with micro/nano-scale for successful wound dressing. Gelatin can mimic the chemical composition, physical structure and structure of the native skin extracellular matrix (ECM). However, the first and main principle in this study is the optimization of parameters of the electrospinning process. The used parameters have a crucial role in obtaining suitable fibers for further cell seeding and cell growth in vitro. With the use of series of various biocompatible polymers and solvents, solutions were tested in various electrospinning settings in order to produce microscale fibers. The scaffolds were analysed with scanning electron microscope images for fiber diameter measurement.

Objective and design: To test whether the hypoxia-inducible factor 1-alpha (HIF1A) axis links transcriptional, cellular, biomarker and host-genetic features of severe COVID-19, in a retrospective multi-scale observational study of public cohorts and one hospital cohort. Material or subjects: 35,268 hospitalized patients (Mexican national registry); 1,100 samples from five bulk RNA-seq cohorts; 25,773 peripheral neutrophils from six individuals; 326 hospitalized patients (São Paulo, Brazil); 93 hospitalized patients (University Clinical Center Kragujevac, Serbia). Treatment: None. Methods: Within-cohort effect sizes for a 10-gene HIF1A panel; single-cell pathway scoring; logistic regression and gradient boosting with SHAP; TaqMan genotyping of HIF1A rs11549465 and rs41508050; cross-validation with bootstrap confidence intervals. Results: HIF1A (mean Cohen’s d +0.39) and LDHA (+0.76) were higher in severe disease in all five cohorts. Neutrophils of all three patients who failed extubation scored higher than those of both weaned patients and over-expressed S100A8/A9. C-reactive protein dominated ICU prediction; laboratory variables raised the AUC from 0.636 to 0.794. In Kragujevac, a clinical model predicted severe outcome (AUC 0.84, 95% CI 0.75–0.92). rs11549465 CT/TT carriers had lower mortality (1/11 vs 28/78; p = 0.095). Conclusions: HIF1A pathway activation is reproducible across cohorts and localizes to an alarmin-rich neutrophil state; host-genetic effects require larger cohorts.