Among the different chemical and physical treatments used to remove the color of the textile effluents, bioremediation offers many benefits to the environment. In this study, we determined the potential of Spirulina platensis (S. platensis) for decolorizing indigo blue dye under different incubation conditions. The microalgae were incubated at different pH (from 4 to 10) to calibrate for the optimal discoloration condition; a pH of 4 was found to be optimal. The biomass concentration in all experiments was 1 g/L, which was able to decolorize the indigo blue dye by day 3. These results showed that S. platensis is capable of removing indigo blue dye at low biomass. However, this was dependent on the treatment conditions, where temperature played the most crucial role. Two theoretical adsorption models, namely (1) a first-order model equation and (2) a second-order rate equation, were compared with observed adsorption vs. time curves for different initial concentrations (from 25 to 100 mg/L). The comparison between models showed similar accuracy and agreement with the experimental values. The observed adsorption isotherms for three temperatures (30, 40, and 50 °C) were plotted, showing fairly linear behavior in the measured range. The adsorption equilibrium isotherms were estimated, providing an initial description of the dye removal capacity of S. platensis.

The use of microalgae has been emerging as a potential technology to reduce greenhouse gases and bioremediate polluted water and produce high-value products as pigments, phytohormones, biofuels, and bioactive compounds. The improvement in biomass production is a priority to make the technology implementation profitable in every application mentioned before. The present study was conducted to explore the use of microalgae from genus Chlorella and Tetradesmus for the generation of substances of interest with UV absorption capacity. A mathematical model was developed for both microalgae to characterize the production of microalgae biomass considering the effects of light intensity, temperature, and nutrient consumption. The model was programmed in MATLAB software, where the three parameters were incorporated into a single specific growth rate equation. It was found that the optimal environmental conditions for each genus (Chlorella T=36°C, and I<787 μmol/m²s; Tetradesmus T=23°C and I<150 μmol/m²s), as well as the optimal specific growth rate depending on the personalized values of the three parameters. This work could be used in the production of microalgae biomass for the design and development of topical applications to replace commercial options based on compounds that compromise health and have a harmful impact on the environment.

Curcumin can enhance cutaneous wound healing by improving fibroblast proliferation. However, its therapeutic properties are dose-dependent: high concentrations produce cytotoxic effects, whereas low concentrations benefit cell proliferation. Similarly, the type of administration and its moderation are key aspects, as an erroneous distribution may result in null or noxious activity to the organism. In silico models for curcumin diffusion work as predictive tools for evaluating curcumin’s cytotoxic effects and establishing therapeutic windows. A 2D fibroblast culture growth model was created based on a model developed by Gérard and Goldbeter. Similarly, a curcumin diffusion model was developed by adjusting experimental release values obtained from Aguilar-Rabiela et al. and fitted to Korsmeyer–Peppas and Peleg’s hyperbolic models. The release of six key curcumin concentrations was achieved. Both models were integrated using Morpheus software, and a scratch-wound assay simulated curcumin’s dose-dependent effects on wound healing. The most beneficial effect was achieved at 0.25 μM, which exhibited the lowest cell-division period, the highest confluence (~60% for both release models, 447 initial cells), and the highest final cell population. The least beneficial effect was found at 20 μM, which inhibited cell division and achieved the lowest confluence (~34.30% for both release models, 447 initial cells). Confluence was shown to decrease as curcumin concentration increased, since higher concentrations of curcumin have inhibitory and cytotoxic effects.