Breast cancer ranks among the most commonly diagnosed cancers worldwide and bears the highest mortality rate. As an integral component of cancer treatment, mastectomy entails the complete removal of the affected breast. Typically, breast reconstruction, involving the use of silicone implants (augmentation mammaplasty), is employed to address the aftermath of mastectomy. To mitigate postoperative risks associated with mammaplasty, such as capsular contracture or bacterial infections, the functionalization of breast implants with coatings of cyclodextrin polymers as drug delivery systems represents an excellent alternative. In this context, our work focuses on the application of a mathematical model for simulating drug release from breast implants coated with cyclodextrin polymers. The proposed model considers a unidirectional diffusion process following Fick’s second law, which was solved using the orthogonal collocation method, a numerical technique employed to approximate solutions for ordinary and partial differential equations. We conducted simulations to obtain release profiles for three therapeutic molecules: pirfenidone, used for preventing capsular contracture; rose Bengal, an anticancer agent; and the antimicrobial peptide KR-12. Furthermore, we calculated the diffusion profiles of these drugs through the cyclodextrin polymers, determining parameters related to diffusivity, solute solid–liquid partition coefficients, and the Sherwood number. Finally, integrating these parameters in COMSOL multiphysics simulations, the unidirectional diffusion mathematical model was validated.

The improper management of fats, oils, and grease (FOG) from food services is a major cause of sewer blockages and environmental damage. This study examines FOG management in the restaurant sector of the Guadalajara Metropolitan Area, Mexico, from three complementary perspectives: the performance of the authorized formal collection system, management practices in food establishments, and the physicochemical characteristics of grease trap residues. These perspectives were addressed using official administrative records and reports from environmental authorities, structured surveys applied to kitchen staff, and laboratory analyses of grease trap samples collected in restaurants. The results reveal important institutional and structural constraints affecting FOG management. Only a limited number of authorized collectors operate actively, serving a small fraction of potential generators, while most food service establishments are micro- or small-sized businesses with limited technical and financial capacity to comply with regulations. A large portion of the sector consists of small, low-cost food service establishments with intensive oil use (e.g., street food vendors, sandwich shops, and set-menu restaurants), which contribute to widespread oil reuse and inadequate disposal practices. Laboratory analyses showed a high free fatty acids (FFAs) content and compositional profiles consistent with repeated oil use, with negative implications for sewer systems and waste management. Overall, the findings highlight the need for stronger regulatory enforcement, collection schemes tailored to micro-scale generators, and awareness campaigns while also indicating opportunities for FOG valorization within circular economy approaches, particularly through energy recovery pathways.

This study presents an ordinary differential equation (ODE) based hybrid kinetic-metabolic model to predict the time evolution of biomass, glucose, hyaluronic acid (HA), and lactic acid during fermentation by Streptococcus equi subsp. zooepidemicus. The model incorporates simplified metabolic pathways and estimates the qualitative dynamics of internal, unmeasured metabolites involved in glycolysis, biomass synthesis, and HA production. Special emphasis is placed on the energetic molecules ATP/ADP, as well as the coenzymes NADH/NAD⁺, which are involved in redox reactions. These molecules have been shown to play regulatory roles in metabolism. The model predictions closely match the experimental data and provide insights into how varying glucose levels affect intracellular metabolic fluxes.