In this work a combined analysis of osmotic injury and cytotoxic effect useful for the optimization of the cryopreservation process of a cell suspension is carried out. The case of human Mesenchymal Stem Cells (hMSCs) from Umbilical Cord Blood (UCB) in contact with DiMethyl SulfOxide (DMSO) acting as Cryo‐Protectant Agent (CPA) is investigated from the experimental as well as the theoretical perspective. The experimental runs are conducted by suspending the cells in hypertonic solutions of DMSO at varying osmolality, system temperature and contact times; then, at room temperature, cells are pelleted by centrifugation and suspended back to isotonic conditions. Eventually cell count and viability are measured by means of a Coulter counter and flow‐cytometer, respectively. Overall, a decrease of cell count and viability results when DMSO concentration, temperature and contact time increase. A novel mathematical model is developed and proposed to interpret measured data by dividing the cell population between viable and non‐viable cells. The decrease of cell count is ascribed exclusively to the osmotic injury caused by expansion lysis: excessive swelling causes the burst of both viable as well as non‐viable cells. On the other hand, the reduction of cell viability is ascribed only to cytotoxicity which gradually transforms viable cells into non‐viable ones. A chemical reaction engineering approach is adopted to describe the dynamics of both phenomena: by following the kinetics of two chemical reactions during cell osmosis inside a closed system it is shown that the simultaneous reduction of cell count and viability may be successfully interpreted. The use of the Surface Area Regulation (SAR) model recently proposed by the authors allows one to avoid the setting in advance of fixed cell Osmotic Tolerance Limits (OTLs), as traditionally done in cryopreservation literature to circumvent the mathematical simulation of osmotic injury. Comparisons between experimental data and theoretical simulations are provided: first, a non‐linear regression analysis is performed to evaluate unknown model parameters through a best‐fitting procedure carried out in a sequential fashion; then, the proposed model is validated by full predictions of system behavior measured at operating conditions different from those used during the best‐fit procedure. This article is protected by copyright. All rights reserved.

This work is on the synthesis and the characterization of natural deep eutectic solvents based on monoterpenoids. Low viscous fluids with suitable physicochemical properties are produced. Therefore, considering their null toxicity, biodegradability, and low cost make them a suitable platform for developing sustainable solvents for various processes and applications. A theoretical study considering quantum chemistry and classical molecular dynamics is reported providing a nanoscopic characterization of structure, dynamics, and hydrogen bonding in the considered fluids. The reported results provide an analysis of the properties of this new family of solvents, thus providing the required information for developing structure–property relationships for proper solvent design into a sustainable chemistry framework.

The protection of natural areas is considered an essential strategy for environment conservation. The objective of this work was to determine the level of vulnerability, considering the characterization and identification of the risk zones and ecological protection of the Pagaibamba Protection Forest (PPF, Peru). To determine the vulnerable areas, Landsat ETM satellite images, topographic, geological, ecological, and vegetation cover maps were used. Geological, physiographic, edaphological, vegetation cover, and land use potential characteristics, were analyzed. Three Ecological Protection and Risk Zones were identified, with the largest extension of the PPF corresponding to lands of very high and high vulnerability and high ecological risk, which include >85% of Protected Natural Areas (PNA) and 54% of the Buffer Zone (BZ). Moderate risk areas represent 30% of the Buffer Zone (BZ) and 13% of the PNA, and the low-risk areas (represent 15% of the BZ and 2% of the PNA). Biogeographically, the PPF was related to the Cloudy Montane Forests Ecoregion of the Andes Mountains, standing out the Tropical Montane Cloud Forest (TMCF) and the Tropical Lower Montane Cloud Forest (TLMCF). These forests are a global conservation priority due to their great biodiversity, high level of endemicity of flora and fauna, and the crucial hydrological function they fulfill.

Carbon nanotubes (CNTs) have attracted the attention of academy and industry due to their potential applications, being currently produced and commercialized at a mass scale, but their possible impact on different biological systems remains unclear. In the present work, an assessment to understand the toxicity of commercial pristine multi-walled carbon nanotubes (MWCNTs) on the unicellular fungal model Saccharomyces cerevisiae is presented. Firstly, the nanomaterial was physico-chemically characterized, to obtain insights concerning its morphological features and elemental composition. Afterwards, a toxicology assessment was carried out, where it could be observed that cell proliferation was negatively affected only in the presence of 800 mg L−1 for 24 h, while oxidative stress was induced at a lower concentration (160 mg L−1) after a short exposure period (2 h). Finally, to identify possible toxicity pathways induced by the selected MWCNTs, the transcriptome of S. cerevisiae exposed to 160 and 800 mg L−1, for two hours, was studied. In contrast to a previous study, reporting massive transcriptional changes when yeast cells were exposed to graphene nanoplatelets in the same exposure conditions, only a small number of genes (130) showed significant transcriptional changes in the presence of MWCNTs, in the higher concentration tested (800 mg L−1), and most of them were found to be downregulated, indicating a limited biological response of the yeast cells exposed to the selected pristine commercial CNTs.

The world desperately needs new technologies and solutions for gas capture and separation. To make this possible, molecular modeling is applied here to investigate the structural, thermodynamic, and dynamical properties of a model for the poly(urethane urea) (PUU) oligomer model to selectively capture CO2 in the presence of CH4. In this work, we applied a well-known approach to derive atomic partial charges for atoms in a polymer chain based on self-consistent sampling using quantum chemistry and stochastic dynamics. The interactions of the gases with the PUU model were studied in a pure gas based system as well as in a gas mixture. A detailed structure characterization revealed high interaction of CO2 molecules with the hard segments of the PUU. Therefore, the structural and energy properties explain the reasons for the greater CO2 sorption than CH4. We find that the CO2 sorption is higher than the CH4 with a selectivity of 7.5 at 298 K for the gas mixture. We characterized the Gibbs dividing surface for each system, and the CO2 is confined for a long time at the gas–oligomer model interface. The simulated oligomer model showed performance above the 2008 Robeson’s upper bound and may be a potential material for CO2/CH4 separation. Further computational and experimental studies are needed to evaluate the material.