Engineering mechanobiology through organoids-on-chip: A strategy to boost therapeutics.

The mechanical environment of living cells is as critical as chemical signaling. Mechanical stimuli play a pivotal role in organogenesis and tissue homeostasis. Unbalances in mechanotransduction pathways often lead to diseases, such as cancer, cystic fibrosis, and neurodevelopmental disorders. Despite its inherent relevance, there is a lack of proper mechanoresponsive in vitro study systems. In this context, there is an urge to engineer innovative, robust, dynamic, and reliable organotypic technologies to better connect cellular processes to organ-level function and multi-tissue cross-talk. Mechanically active organoid-on-chip has the potential to surpass this challenge. These systems converge microfabrication, microfluidics, biophysics, and tissue engineering fields to emulate key features of living organisms, hence, reducing costs, time, and animal testing. In this review, we intended to present cutting-edge organ-on-chip platforms that integrate biomechanical stimuli as well as novel multicellular culture, such as organoids. We focused on its application in two main fields: precision medicine and drug development. Moreover, we also discussed the state of the art for the development of an engineered model to assess patient-derived tumor organoid metastatic potential. Finally, we highlighted the current drawbacks and emerging opportunities to match the industry needs. We envision the use of mechanoresponsive organotypic-on-chip microdevices as an indispensable tool for precision medicine, drug development, disease modeling, tissue engineering, and developmental biology.

Hybrid integral transform analysis of supercooled droplets solidification.

The freezing phenomena in supercooled liquid droplets are important for many engineering applications. For instance, a theoretical model of this phenomenon can offer insights for tailoring surface coatings and for achieving icephobicity to reduce ice adhesion and accretion. In this work, a mathematical model and hybrid numerical-analytical solutions are developed for the freezing of a supercooled droplet immersed in a cold air stream, subjected to the three main transport phenomena at the interface between the droplet and the surroundings: convective heat transfer, convective mass transfer and thermal radiation. Error-controlled hybrid solutions are obtained through the extension of the generalized integral transform technique to the transient partial differential formulation of this moving boundary heat transfer problem. The nonlinear boundary condition for the interface temperature is directly accounted for by the choice of a nonlinear eigenfunction expansion base. Also, the nonlinear equation of motion for the freezing front is solved together with the ordinary differential system for the integral transformed temperatures. After comparisons of the solution with previously reported numerical and experimental results, the influence of the related physical parameters on the droplet temperatures and freezing time is critically analysed.

Mathematical Parameters of the COVID-19 Epidemic in Brazil and Evaluation of the Impact of Different Public Health Measures.

A SIRU-type epidemic model is employed for the prediction of the COVID-19 epidemy evolution in Brazil, and analyze the influence of public health measures on simulating the control of this infectious disease. The proposed model allows for a time variable functional form of both the transmission rate and the fraction of asymptomatic infectious individuals that become reported symptomatic individuals, to reflect public health interventions, towards the epidemy control. An exponential analytical behavior for the accumulated reported cases evolution is assumed at the onset of the epidemy, for explicitly estimating initial conditions, while a Bayesian inference approach is adopted for the estimation of parameters by employing the direct problem model with the data from the first phase of the epidemy evolution, represented by the time series for the reported cases of infected individuals. The evolution of the COVID-19 epidemy in China is considered for validation purposes, by taking the first part of the dataset of accumulated reported infectious individuals to estimate the related parameters, and retaining the rest of the evolution data for direct comparison with the predicted results. Then, the available data on reported cases in Brazil from 15 February until 29 March, is used for estimating parameters and then predicting the first phase of the epidemy evolution from these initial conditions. The data for the reported cases in Brazil from 30 March until 23 April are reserved for validation of the model. Then, public health interventions are simulated, aimed at evaluating the effects on the disease spreading, by acting on both the transmission rate and the fraction of the total number of the symptomatic infectious individuals, considering time variable exponential behaviors for these two parameters. This first constructed model provides fairly accurate predictions up to day 65 below 5% relative deviation, when the data starts detaching from the theoretical curve. From the simulated public health intervention measures through five different scenarios, it was observed that a combination of careful control of the social distancing relaxation and improved sanitary habits, together with more intensive testing for isolation of symptomatic cases, is essential to achieve the overall control of the disease and avoid a second more strict social distancing intervention. Finally, the full dataset available by the completion of the present work is employed in redefining the model to yield updated epidemy evolution estimates.

Integral transform analysis of radionuclide transport in variably saturated media using a physical non-equilibrium model: application to solid waste leaching at a uranium mining installation.

The Generalized Integral Transform Technique (GITT) was employed to simulate transient one-dimensional flow in variably saturated porous media, as well as radioactive waste transport within different layers (a solid waste pile, nearby soil, and a granular aquifer) towards the edge of a uranium mining installation under institutional control. Computational codes, written using the Mathematica software system, were implemented and tested for solution of the coupled advection-dispersion equations for an arbitrary number of daughter products within a radioactive chain migrating in saturated and unsaturated soil layers. The computer simulations were verified in great detail against results obtained using the built-in routine NDSolve of the Mathematica platform and the HYDRUS-1D software system. The present work reports the main results for 238U chain radionuclide transport using data extracted from a safety assessment of solid waste repositories at a uranium mining and milling installation in Caetité, state of Bahia, Brazil, operated by INB (Indústrias Nucleares do Brasil). Concentration evolutions of the various radionuclides obtained with the simulations were analyzed for five different cases to explore variations in the infiltration and recharge rates, the effect of assuming physical equilibrium or non-equilibrium transport conditions, and of different initial concentrations of some of the radionuclides.